**OUR STORY**\n\nWe’re on a mission to build solutions for the next generation of commerce. Ultimately we enable developers and platforms to make commerce seamless by connecting them to millions of merchants and billions of products with a single API.\n\nCarted will power commerce experiences anywhere on the internet, allowing developers and content creators to build a direct checkout of any product from any merchant via any content on the web.\n\n**We are looking for Machine Learning Engineers to join our team and come help us solve data-driven problems at Petabyte scale.**\n\n**REQUIREMENTS**\n* Python, TensorFlow/PyTorch.\n* NLP (problems include entity extraction, intent classification, sentence classification).\n* Is well-aware of the current state of research in the domain (representation learning) and comfortable with implementing new ideas when needed.\n* ML Solution engineering experience with any of the following cloud service providers: Google Cloud * Platform, Microsoft Azure, Amazon Web Services.\n* Vector similarity search at scale with open-source tools like ScaNN, Faiss, Annoy, etc.\n* Computer vision (problems include fine-grained image classification, localization, etc.)\n\n**BONUS POINTS**\n* Experience with handling e-commerce data.\n* Docker and k8s.\n* Exposing ML models as gRPC/RESTful APIs or with fully managed serverless systems.\n* Has trained deep neural networks using distributed training for large datasets using TPUs.\n* Deployed ML model / NLP models / computer vision models that are currently in production.\n\n**WHY COME AND JOIN OUR TEAM**\n\nWe are a well-funded, fast growing startup with people around the globe. You will have autonomy and ownership of the work you do, with flexible hours\n\nWe offer a competitive base salary plus equity, so you are rewarded for your best work. On top of this we offer generous paid holidays. Holiday is called holiday at Carted and never ‘annual leave’ as we are big believers that holiday is your time and we want you to enjoy it! We also provide you with top-end equipment to make your space enjoyable.\n\nWe have a training and development allowance to invest in your personal and professional development.\n\nWe like to learn quickly, do things differently and most importantly, have fun! \n \n\nPlease mention the word **PEPPED** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4yNDM=). This is a feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.\n\n \n\n#Salary and compensation\n $100,000 — $200,000/year\n \n\n#Location\nWorldwide

**The Role**\n\nAs a member of the Autopilot AI Tooling team you will design and implement a diverse set of tools that power our machine learning workflows. You will work closely with some of the best, world-class AI researchers and machine learning experts towards Tesla’s goal of a self-driving future. \n\nThe AI Tooling team is a central part of Autopilot AI. The systems you build will have a large impact on the entire lifecycle of model development. This includes data processing, data discovery, annotation, and visualization. This also includes tools that help us automate the entire workflows of training, validation, and productionization of our Autopilot neural networks. \n\nAs an engineer on the AI Tooling team, you bring top-notch software engineering skills and can contribute to our tooling systems immediately. Knowledge of machine learning, computer vision, or neural networks is a plus but not required. That can be learned on the job as you work with our machine learning experts. A strong candidate for the AI Tooling team will either be an excellent software generalist, or someone who is exceptionally strong in either backend or frontend engineering.\n\n**Responsibilities**\n\nDesign and implement large-scale data processing pipelines that handle a diverse set of Autopilot related data such as images, sensor inputs, and human labels.\nDesign and implement tools, tests, metrics, and dashboards to accelerate the development cycle of our model training.\nWork closely with frontend engineers to seamlessly integrate with backend systems.\nWork closely with AI researchers to support evolving research projects and implement new production features.\n\n**Requirements**\n\nBS/MS in Computer Science or related field, or equivalent industry experience.\nStrong knowledge of at least one programming language related to data engineering, such as Python or Scala is required.\nExperience with scientific computing libraries such as numpy, pandas, or scikit-learn is a plus.\nExperience with big data systems such as Spark, Hadoop/MapReduce is a plus.\nExperience with cloud computing such AWS EC2/S3/RDS is a plus.\nExperience with ElasticSearch or other scalable search systems is a plus.\nExperience with real-time data processing is a plus.\nKnowledge of machine learning, computer vision, or neural networks is a plus but not required.\nTesla participates in the E-Verify Program\n\nTesla is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state or local laws.\n\nTesla is also committed to working with and providing reasonable accommodations to individuals with disabilities. Please let your recruiter know if you need an accommodation at any point during the interview process. \n\nPlease mention the words **FOREST SHED CERTAIN** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4yNDM=). This is a feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.\n\n \n\n#Location\nPalo Alto, Austin or Remote

 **Overview:**\n\nThe legal cannabis market is one of the most dynamic, fast-paced new industries on the planet. Growing adoption for recreational as well as medical use will require public perceptions to shift and evolve— a massive marketing challenge that has to take into account compliance with multiple states and federal regulatory bodies for trade/communications as well as restrictions on fundamental ad channels taken for granted by traditional consumer product marketers.\n\nThose who will succeed in building enduring, global cannabis brands need tools to navigate problems unique to the space. This is why AMNESIA builds products that help the top, enterprise-size cannabis brands compliantly scale their digital marketing and reach the masses with the broader mission of empowering cannabis communities to positively grow.\n\n**The Role:**\n\nAMNESIA is seeking a Senior Full Stack Developer that has a solid foundation in Machine Learning and NLP to join our team on a contract basis.\n\nYou'll collaborate closely with the founders and product team to understand our customers' problems as well as to plan, strategize, & help to develop our enterprise marketing compliance product from closed beta stage to version one. \n\nYou will be responsible for our entire ML/NLP pipeline from ideation to final implementation in order to level up the core feature sets of our compliance product. \n\nYou should have experience building scalable/maintainable complex systems. You should have experience building intuitive products that empower users. You should be able to do all of the above quickly and more efficiently than most.\n\nFounders are veterans of regulated markets who move quickly and are passionate about their work. Our partners and customers are the cream of the crop of the cannabis industry. This role offers huge room for growth for an aggressive and ambitious individual who is excited to work with the founders to take ownership of the core feature-sets in our new product and making a dent in one of the most exciting new industries in the world.\n\n**This is a fully remote position.** \n\n**Responsibilities**\n\n- Architect, design, and hands-on build the software\n- Work closely with the founders and product team to build and implement ML/NLP models to improve our product experience.\n- Prepares datasets to train and validate models.\n- Understands and interprets data to come up with optimal feature sets.\n- Deploys the machine learning algorithms into production environment.\n- Documents and presents the work in a complete and consistent way.\n- Produce clean, well-documented and efficient code\n- Handle automation, infrastructure and orchestration\n- Brainstorm new features and shape the product road map together with the founding team and clients\n\n**Requirements:**\n\n- 3+ years experience with machine learning, computer vision, & natural language processing required\n- Ability to lead the implementation of machine learning models from problem definition to serving it in production.\n- expertise in algorithms and data structure\n- expertise in building APIs and back-end business logic\n- experience working with Python/Django\n- experience with AWS, Google Cloud\n- experience working with React is preferred\n- Great communication & documentation skills in English - both oral and written\n- You are extremely proactive, independent and comfortable with proposing new ideas — and holding your ground when you believe you are right.\n\n**Bonus:**\n\n- experience developing Enterprise SaaS products\n- experience with NLP models for processing biomedical, scientific or clinical text\n- You significantly contributed to building an early stage product\n- You were the first engineer or the lead engineer in a venture funded startup\n- experience working with docker/containers and\n- experience with data engineering tools and containerization\n- experience using system monitoring tools and automated testing frameworks\n\n**What We Value:**\n\n- A high bar for quality of code and quality of user experience\n- Ability to collaborate, iterate, and empathize with a variety of individuals (users and technical / non-technical stakeholders).\n- Extreme curiosity, growth mindset, and ability to learn quickly and work independently.\n- You are keen on learning new methodologies, technologies and tools; also, on evaluating their pros and cons. You ask questions; always eager to learn more. But you are also pragmatic.\n- Ability to think through customer requirements to come up with creative and high-impact ways of solving their problems \n\nPlease mention the words **OVAL DUTY LAUGH** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4yNDM=). This is a feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.\n\n \n\n#Salary and compensation\n $80,000 — $130,000/year\n \n\n#Location\nWorldwide

Thoughtexchange empowers organizations to lead group discussions about things that matter. Leaders from all over North America inform critical decisions with powerful, patent pending analytics and visualizations supported by our software and world class customer success team.  Millions of thoughts have been shared and rated on the Thoughtexchange platform and with a fresh round of financing Thoughtexchange is ready to scale.\n\nWe are looking for a creative and passionate Machine Learning Engineer wanting to work on a product that makes a difference. You will join a highly motivated and talented research engineering team who work with tools on the cutting edge of technology.  Our team keenly observes technology trends but strives to balance practical business concerns with technical requirements. We are an inclusive team where everyone treats each other with extraordinary respect.\n\n\n\n\nResponsibilities:\n\n\n\n\n* Create proof of concept of machine learning products and services using open source tools, libraries and frameworks\n\n* Detect patterns associated with our massive text and raw data to generate models enabling our customers with recommended actions and predicted results\n\n* Work closely with R&D team. Train and develop machine learning models with a focus on NLP and recommender systems based on business requirements\n\n* Be able (and willing) to multi-task and learn new technologies quickly\n\n\n\n\n\n\n\n\n\n\nQualifications:\n\n\n\n\n* Masters in Computer Science, Mathematics, Physics, Electrical Engineering, or equivalent\n\n* 3+ years experience in the industry\n\n* Experience in training, deploying, testing and shipping ML models in a production environment\n\n* Solid understanding and applying object-oriented design, data structures, algorithm design, and complexity analysis\n\n* Deep understanding on machine learning, deep learning and natural language processing\n\n* Experience in deep learning frameworks, e.g. Tensorflow, Pytorch, Keras, Scikit Learn\n\n* Experience in transformer language models such as BERT, BART and GPT for various downstream tasks\n\n* Passionate about keeping up with the state of the art and constantly learning as the field evolves\n\n* Familiar with recommender systems\n\n* Solid Python programming skills\n\n* Excellent oral and written communication and presentation skills\n\n* Self starter, quick learner and creative mind\n\n\n\n\n\n\n\n\n\n\nNice to have:\n\n\n\n\n* Candidates with a PhD\n\n* Familiarity with Big Data tools such as Hadoop and Spark\n\n* Proven track record of publishing in top tier ML conferences such as NeurIPS, ICML, etc\n\n\n\n\n \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Machine Learning, Engineer and Python jobs that are similar:\n\n $80,000 — $130,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n

**About Us**\n\nNannyML is an early stage venture funded start-up. At NannyML we build enterprise software for supervising and correcting ML systems in production. That includes detecting data and concept drift, estimating performance loss and suggesting corrective actions as well as a dashboard that presents all these insights for business and technical users. Our goal is to ensure that ML systems keep adding value and that insights that can be extracted from ML systems are clearly communicated to business stakeholders. We want to make ML in production effortless to interact with and extract value from.\n\n\n\n**About the Role**\n\nWe are looking for a Senior Software Engineer to architect and build a great product. You will be working closely with the founding team. Our expertise is in leveraging business information, exploiting data and prototyping data solutions. Your expertise comes in to complement the team: you will be responsible for product development from the software and data engineering side: from designing engineering processes, brainstorming with the founders, through prototyping and first implementation to architectural choices and frameworks. You will have the ownership and the decision making power to shape everything that lies between product and research. As we grow NannyML we expect you to grow with us. We envision your path may grow your position into VP of engineering or similar.\n\nWe are an early stage startup, and so you will wear many hats and be expected to do what's needed for the company to succeed, including working on things that you don't know anything about and at weird times from time to time — we all are. You will have the opportunity to get meaningfully involved in the areas of product, engineering, hiring and people management among others.\n\nWe value freedom with responsibility, transparency and a growth mindset. We believe in generating our own luck by trying out new stuff, always asking, constantly learning, reading and meeting new people with different world-views. We value trying new things, and appreciate that from time to time things may break in the process. Working at NannyML you will have full autonomy to make impactful decisions and prioritise and organise your work the way you see fit.\n\n**Please do not apply for this role if you are not physically located in Europe, Africa or the Middle East (UTC-2 to UTC+3) or you are not fully willing to relocate immediately. This is a fully remote position, however we will be working with you very closely, so significant work hours overlap is necessary. You also need to be able to fly to Belgium or Portugal as needed.**\n\nExperience with early stage product is absolutely necessary. If you don't have such experience please do not apply. Please bear in mind that this is not a web development position, while web development might be a small part of what you do, it is not going to be your main focus.\n\n**Responsibilities**\n\n* Integrate and productionize Data Drift detection and prediction algorithms\n* Develop and deliver CI/CD, version control and testing frameworks\n* Brainstorm new features and shape the product road map together with the founding team and clients\n* Architect, design, and hands-on build the software\n* Produce clean, well-documented and efficient code\n* Handle automation, infrastructure and orchestration\n* Help with implementing NannyML at clients and with clients on-boarding\n\n**Requirements**\n\n**Basic**\n\n* You significantly contributed to building an early stage product\n* You have experience working with data (such as ML systems, big data or building data heavy products like BI tools)\n* Great communication skills in English - both oral and written\n* You are extremely proactive, independent and comfortable with proposing new ideas — and holding your ground when you believe you are right.\n* Strong experience with Python in back-end development, infrastructure or data engineering\n* 5+ years working as a Software Engineer or in a similar role\n* You live in or are willing and able to relocate to EU time zones\n\n**Bonus points**\n\n* You were the first engineer or the lead engineer in a venture funded startup\n* Experience with data engineering tools and containerization\n* Experience using system monitoring tools and automated testing frameworks\n* Experience building enterprise grade software\n* Significant experience with on-premise deployment and integration with enterprise IT systems.\n* Basic familiarity with Machine Learning\n* Masters degree in a STEM related field\n\n**Benefits**\n\n* Fully Remote Working Environment\n* 23+ Days of Planned Leave Annually\n* Paid sick leave and private healthcare plan\n* We support paid parental leave\n* Home office, work and well-being allowances (for yoga, gym etc.) and other nice benefits\n* Stock option plan\n* Salary: 54,000 - 66,000 EUR/year\n \n\nPlease mention the words **ZOO SPATIAL MOTOR** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4yNDM=). This is a feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.\n\n \n\n#Salary and compensation\n $49,000 — $78,000/year\n \n\n#Location\nEurope, Africa or the Middle East (UTC-2 to UTC+3)

**About Us**\n\nNannyML is an early stage venture funded start-up. At NannyML we build enterprise software for supervising and correcting ML systems in production. That includes detecting data and concept drift, estimating performance loss and suggesting corrective actions as well as a dashboard that presents all these insights for business and technical users. Our goal is to ensure that ML systems keep adding value and that insights that can be extracted from ML systems are clearly communicated to business stakeholders. We want to make ML in production effortless to interact with and extract value from.\n\n\n\n**About the Role**\n\nWe are looking for a Senior Software Engineer to architect and build a great product. You will be working closely with the founding team. Our expertise is in leveraging business information, exploiting data and prototyping data solutions. Your expertise comes in to complement the team: you will be responsible for product development from the software and data engineering side: from designing engineering processes, brainstorming with the founders, through prototyping and first implementation to architectural choices and frameworks. You will have the ownership and the decision making power to shape everything that lies between product and research. As we grow NannyML we expect you to grow with us. We envision your path may grow your position into VP of engineering or similar.\n\nWe are an early stage startup, and so you will wear many hats and be expected to do what's needed for the company to succeed, including working on things that you don't know anything about and at weird times from time to time — we all are. You will have the opportunity to get meaningfully involved in the areas of product, engineering, hiring and people management among others.\n\nWe value freedom with responsibility, transparency and a growth mindset. We believe in generating our own luck by trying out new stuff, always asking, constantly learning, reading and meeting new people with different world-views. We value trying new things, and appreciate that from time to time things may break in the process. Working at NannyML you will have full autonomy to make impactful decisions and prioritise and organise your work the way you see fit.\n\n**Please do not apply for this role if you are not physically located in Europe, Africa or the Middle East (UTC-2 to UTC+3) or you are not fully willing to relocate immediately. This is a fully remote position, however we will be working with you very closely, so significant work hours overlap is necessary. You also need to be able to fly to Belgium or Portugal as needed.**\n\nExperience with early stage product is absolutely necessary. If you don't have such experience please do not apply. Please bear in mind that this is not a web development position, while web development might be a small part of what you do, it is not going to be your main focus.\n\n**Responsibilities**\n\n* Integrate and productionize Data Drift detection and prediction algorithms\n* Develop and deliver CI/CD, version control and testing frameworks\n* Brainstorm new features and shape the product road map together with the founding team and clients\n* Architect, design, and hands-on build the software\n* Produce clean, well-documented and efficient code\n* Handle automation, infrastructure and orchestration\n* Help with implementing NannyML at clients and with clients on-boarding\n\n**Requirements**\n\n**Basic**\n\n* You significantly contributed to building an early stage product\n* You have experience working with data (such as ML systems, big data or building data heavy products like BI tools)\n* Great communication skills in English - both oral and written\n* You are extremely proactive, independent and comfortable with proposing new ideas — and holding your ground when you believe you are right.\n* Strong experience with Python in back-end development, infrastructure or data engineering\n* 5+ years working as a Software Engineer or in a similar role\n* You live in or are willing and able to relocate to EU time zones\n\n**Bonus points**\n\n* You were the first engineer or the lead engineer in a venture funded startup\n* Experience with data engineering tools and containerization\n* Experience using system monitoring tools and automated testing frameworks\n* Experience building enterprise grade software\n* Significant experience with on-premise deployment and integration with enterprise IT systems.\n* Basic familiarity with Machine Learning\n* Masters degree in a STEM related field\n\n**Benefits**\n\n* Fully Remote Working Environment\n* 23+ Days of Planned Leave Annually\n* Paid sick leave and private healthcare plan\n* We support paid parental leave\n* Home office, work and well-being allowances (for yoga, gym etc.) and other nice benefits\n* Stock option plan\n \n\nPlease mention the words **OBEY SCIENCE HAMMER** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4yNDM=). This is a feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.\n\n \n\n#Salary and compensation\n $49,000 — $78,000/year\n \n\n#Location\nEurope, Africa or the Middle East (UTC-2 to UTC+3)

[NEURONBITS](http://neuronbits.com) is going through an extensive growth fase. We are looking for people who are sharp, creative and hardworking, with an unwavering desire to be the best. In return we provide a competetive compensation package, a friendly, challenging, and motivating working environment.\n\n**All positions at Neuronbits are fully remote**\n\nRenumeration package\n\n- € 50k - 70k / year\n- 25 days paid holidays\n\n\n**Job description**\n\nAs a Senior NLP (Natural Lanague Processing) engineer at Nueronbits you will be responsible for research and development of software which will produce analytics over hundreds of thousands of documents each day, all in real-time. You will be working within a skilled development team, with experts in languages such as Python, C++ and Java, also you will also be working closely with our Data Science team.\n\n\n**Primary responsibilities:**\n\n- Design and developing scalable Machine Learning & AI solutions for processing big amounts of textual data.\n\n- Handle multiple sources of data and effective data manipulation, automating it where possible.\n\n- Research state-of-the-art NLP models.\n\n- Implement NLP models and ensure that they will work with low latency and high accuracy in real-time.\n\n- Write and maintain tools that help to create, deploy, evaluate, and monitor ML models in an effective manner.\n\n\n**Ideally, you’ll have:**\n\n- Degree in Computer Science, Engineering or a related subject.\n\n- Good knowledge of Natural Language Processing techniques and models.\n\n- Experience designing and implementing Neural Networks.\n\n- Experience working with TensorFlow / Keras or similar tools.\n\n- Adaptable and willing to learn new technologies independently.\n\n- Good documentation and communication skills. \n\nPlease mention the words **OMIT DESTROY LATER** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4yNDM=). This is a feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.\n\n \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Machine Learning, Senior, Engineer, Developer and Digital Nomad jobs that are similar:\n\n $60,000 — $130,000/year\n \n\n#Location\nWorldwide

\nZeroEyes was founded by military special operations veterans, self-starters, and elite technologists. Our mission is to prevent gun violence and mass shootings by leveraging Artificial Intelligence.\n\n\nWe are recruiting those interested in joining an extremely high growth startup. If you are searching for a job that asks of you the bare minimum, please do not apply. Your position, perseverance, and skillset are crucial to our mission success. You will be asked to break new ground. We are not looking for passion; we are looking for obsession in our mission to save lives. If you lack the minimum requirements, but believe you are the right candidate, please apply and let us know why you are still a fit. We look forward to speaking with you.\n\n\nIf you are missing some of the skills but believe you are the right candidate, tell us why.\n\n\nResponsibilities:\n\n\n* Build and manage our AI development and operations infrastructure\n\n* Optimize deep learning computer vision training and testing environments\n\n* Visualize training outputs and experiment data in WandB, Tableau, etc.\n\n* Design and automate experiments and data capture methods\n\n* Strategically guide developers and stakeholders as AI SME during new product development\n\n* Develop APIs and integrations that enable our AI models to communicate with partners and customers\n\n* Implement measures to protect our models and data pipelines\n\n* Stay up to date on latest AI research\n\n\n\n\n\nSkills and Experience:\n\n\n* At least 5 years hands-on programming experience working on enterprise products.\n\n* Demonstrated proficiency in multiple programming languages with a strong foundation in a statistical platform such as Python, R, Julia or MatLab.\n\n* Experience building AI models in platforms such as Caffe, TensorFlow or PyTorch\n\n* Installing Nvidia drivers, Cuda, cuDNN\n\n* Linux, Kubernetes and Helm Charts\n\n* Experience with AWS, GCP, Azure, etc a plus\n\n* OpenCV, Nvidia Docker \n\n* Deepstream SDK, TensorRT\n\n* Agile/Jira, Github\n\n\n\n\n\nThis is not a research role. If your only software experience is quickly hacking Python models using libraries like Numpy and Pandas this job isn’t for you.\n\n\nBe ready to show us models you have created and discuss them in great detail.\n\n\nYou will be required to deploy software into production by building maintainable, readable, modular solutions using modern software engineering best practices. Be ready to talk about your experiences doing code reviews, building interfaces, and deployment systems. You should have strong opinions about best software engineering practices. \n\n\nPlease send resumes to [email protected] \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Machine Learning, Engineer and Python jobs that are similar:\n\n $80,000 — $130,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n

\nMachine Learning Engineer\n\nWe are the company behind WordPress.com, Jetpack, WooCommerce and Tumblr. We are looking for someone to join a team of data scientists and software engineers to build, deploy, and iterate on applications involving time series analysis, machine learning, natural language processing and/or search. \n\nWhat have we worked on recently?\n\nWe help our users to create powerful sites with ease and enable our colleagues to support our users. Our completed and ongoing projects include\n\n\n* Elfbot – a machine learning project to automatically tag chat transcripts from our live chat user support. \n\n* Automated anomaly detection on business and user data.\n\n* A new Jetpack Search experience with instant search and improved relevance.\n\n* A generalized machine learning pipeline to build audiences for marketing and engagement.\n\n\n\n\nHow do we work?\n\n\n* We’re kind to each other and our users – we strive to build a positive, supportive, and inclusive culture of cohesive teams focused on delivering value to our customers.\n\n* We work as a global and distributed workforce resulting in a unique way of working built around our creed. \n\n* We offer flexible work arrangements allowing our team members to work when they feel best.\n\n* We welcome collaboration, and you can be involved in any discussion across our many communication channels.\n\n\n\n\nEnough about us, let‘s talk more about you. The Machine Learning Engineer position might be a good fit if you:\n\n\n* Have hands-on experience in building and deploying data-intensive applications to production. You care about building reliable and testable infrastructure and pipelines. Familiarity with the Hadoop ecosystem and cloud computing services like AWS and GCP will be advantageous.\n\n* Are motivated to propose technical solutions, own software architecture, evaluate technologies and infrastructure, or develop technical roadmaps for future applications. \n\n* Have a demonstrated interest in understanding machine learning techniques and workflows like data preprocessing, feature extraction, and training and evaluation of classification and regression models.\n\n* Bring programming skills in multiple programming languages and paradigms. You are likely to encounter Python, PHP, Scala, and SQL in this role and the idea of using them on a regular basis should not be a blocker for you.\n\n* Are familiar with professional software engineering methods and standards such as coding conventions, code reviews, continuous integration, build processes, testing, and operations.\n\n* Are open and able to travel 3-4 weeks per year to meet your teammates in person. We hold an annual all-company meeting every year, and meet up with our teams for a week once or twice per year.\n\n\n\n\nLike all positions at Automattic, you’ll work remotely, and can be based wherever you live.\n\nABOUT AUTOMATTIC\n\nWe are the people behind WordPress.com, WooCommerce, Jetpack, Simplenote, Longreads, VaultPress, Akismet, Gravatar, Crowdsignal, Cloudup, and more. We believe in making the web a better place.\n\nWe’re a distributed company with more than 1100 Automatticians in 65+ countries speaking 75+ different languages. Our common goal is to democratize publishing so that anyone with a story can tell it, regardless of income, gender, politics, language, or where they live in the world.\n\nWe believe in Open Source and the vast majority of our work is available under the GPL.\n\nDIVERSITY & INCLUSION AT AUTOMATTIC\n\nWe’re improving diversity in the tech industry. At Automattic, we want people to love their work and show respect and empathy to all. We welcome differences and strive to increase participation from traditionally underrepresented groups. Our D&I committee involves Automatticians across the company and drives grassroots change. For example, this group has helped facilitate private online spaces for affiliated Automatticians to gather and helps run a monthly D&I People Lab series for further learning. Diversity and Inclusion is a priority at Automattic, though our dedication influences far more than just Automatticians: We make our products freely available and translate our products into and offer customer support in numerous languages. We require unconscious bias training for our hiring teams and ensure our products are accessible across different bandwidths and devices. Read more about our dedication to diversity and inclusion.\n\nHOW TO APPLY\n\nDoes this sound interesting? If yes, click the Apply link below and fill out our application form. In your cover letter, let us know what you can contribute to the team. Proofread! Make sure you spell and capitalize WordPress and Automattic correctly. We are lucky to receive many applications for this position, so try to make your application stand out.\n\nApply for this Job\n\nIf you’re reading this on a site other than automattic.com please ensure you visit automattic.com/work-with-us for the latest details on applying. \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Machine Learning, Engineer, Cloud, Travel and Marketing jobs that are similar:\n\n $70,000 — $120,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n

San Francisco, CA or Remote\n\n\n\nSummary\n\nThe Scoring Platform team builds and maintains machine learning technologies to empower millions of users – readers, contributors, and donors – who contribute to Wikipedia and its sister projects on a daily basis.  We address process inefficiencies with machine learning technologies, we design and test new technology, we produce empirical insights, and we publish and present research on the intersection of technology and culture. We are strongly committed to principles of transparency, privacy and collaboration.  We use free and open source technology and we collaborate with researchers in the industry and academia. \n\nAs a Software Engineer of the Scoring Platform team, you will help us build and scale our machine prediction service, train new machine learning models, and implement other data-intensive applications. You’ll travel to conferences to interact with researchers and volunteer contributors to Wikimedia Projects. You’ll help translate abstractions from current research and volunteers’ needs into concrete technologies and we’ll learn about the impacts of those technologies together.\n\nYou are responsible for:\n\n\n* Implementing the Scoring Platform’s data intensive infrastructure and APIs\n\n* Collaborating with researchers and product managers to bring forward foundational technologies for new products\n\n* Coordinating and communicating with other members of the Wikimedia engineering teams on relevant projects\n\n* Engaging with internal documentation efforts and inform other staff in various aspects of Scoring Platform infrastructure and services\n\n* Working in coordination with volunteer developers, editors, and researchers to understand their needs. \n\n* Sharing our values, respect our code of conduct, adhere to our team norms, and work in accordance with all three\n\n\n\n\nSkills and Experience:\n\n\n* Experience with web programming languages (PHP, Javascript, Python, etc.) \n\n* Understanding or willingness to learn basic statistics, machine learning, and/or data analysis techniques.\n\n* Demonstrable experience developing and debugging web applications\n\n* Strong verbal and written proficiency with the English language\n\n* BS, MS, or PhD in Computer Science, Mathematics, Information science, or equivalent work experience\n\n\n\n\nQualities that are important to us:\n\n\n* Engineering mindset and strong experience in Linux ecosystems\n\n* Real world experience writing horizontally scalable web applications\n\n\n\n\nAdditionally, we’d love it if you have:\n\n\n* Experience participating in open source software projects and communities\n\n* Familiarity with scientific computing libraries in Python\n\n* Experience with web UI development (Javascript, HTML, CSS)\n\n* Experience working with collaborating in online spaces (chatrooms, web forums, etc.)\n\n\n\n\n\nThe Wikimedia Foundation is... \n\n...the nonprofit organization that hosts and operates Wikipedia and the other Wikimedia free knowledge projects. Our vision is a world in which every single human can freely share in the sum of all knowledge. We believe that everyone has the potential to contribute something to our shared knowledge, and that everyone should be able to access that knowledge, free of interference. We host the Wikimedia projects, build software experiences for reading, contributing, and sharing Wikimedia content, support the volunteer communities and partners who make Wikimedia possible, and advocate for policies that enable Wikimedia and free knowledge to thrive. The Wikimedia Foundation is a charitable, not-for-profit organization that relies on donations. We receive financial support from millions of individuals around the world, with an average donation of about $15. We also receive donations through institutional grants and gifts. The Wikimedia Foundation is a United States 501(c)(3) tax-exempt organization with offices in San Francisco, California, USA.\n\nThe Wikimedia Foundation is an equal opportunity employer, and we encourage people with a diverse range of backgrounds to apply.\n\nU.S. Benefits & Perks*\n\n\n* Fully paid medical, dental and vision coverage for employees and their eligible families (yes, fully paid premiums!)\n\n* The Wellness Program provides reimbursement for mind, body and soul activities such as fitness memberships, baby sitting, continuing education and much more\n\n* The 401(k) retirement plan offers matched contributions at 4% of annual salary\n\n* Flexible and generous time off - vacation, sick and volunteer days, plus 19 paid holidays - including the last week of the year.\n\n* Family friendly! 100% paid new parent leave for seven weeks plus an additional five weeks for pregnancy, flexible options to phase back in after leave, fully equipped lactation room.\n\n* For those emergency moments - long and short term disability, life insurance (2x salary) and an employee assistance program\n\n* Pre-tax savings plans for health care, child care, elder care, public transportation and parking expenses\n\n* Telecommuting and flexible work schedules available\n\n* Appropriate fuel for thinking and coding (aka, a pantry full of treats) and monthly massages to help staff relax\n\n* Great colleagues - diverse staff and contractors speaking dozens of languages from around the world, fantastic intellectual discourse, mission-driven and intensely passionate people\n\n\n\n\n*Eligible international workers' benefits are specific to their location and dependent on their employer of record \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Machine Learning, Engineer, Developer, Digital Nomad, English, Education, Travel and Linux jobs that are similar:\n\n $70,000 — $120,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n

\nOur homes are our most valuable asset and also the most difficult to buy and sell. Knock is on a mission to make trading in your house as simple and certain as trading in your car. Started by founding team members of Trulia.com (NYSE: TRLA, acquired by Zillow for $3.5B), Knock is an online home trade-in platform that uses data science to price homes accurately, sell them quickly and guide the customer every step of the way. We share the same top-tier investors as iconic brands like Netflix, Tivo, Match, HomeAway and Houzz.\n\n\nWe’re seeking a Senior Machine Learning Engineer to join us in building our predictive models and our data science team. You will get to work with some of the most interesting data sets and have the freedom and responsibility to help shape our core products from initial data exploration to production models. You will design and implement the foundation of our predictive models and work closely with other team members to test the accuracy in local markets.\n\n\nAt Knock, we have fun, we move fast, we support and celebrate our fellow teammates, and we live by our POPSICLE values.\n\n\nAs a Sr. Machine Learning Engineer you will: \n\n\n* Design and develop models that produce insights from residential real estate data.\n\n* Develop, train, test, deploy and iterate on modeling approaches and methodologies.\n\n* Evaluate, improve and iterate on the performance of existing ML models.\n\n* Explore and recommend new data to improve model outputs.\n\n* Apply and integrate model predictions to our new and existing products.\n\n* Communicate model outcomes to the broader team.\n\n\n\n\n\nWe’re looking for Knockstars who have: \n\n\n* Must be U.S. based.\n\n* MS or higher in Computer Science, Statistics, Mathematics or equivalent.\n\n* Experience applying existing or novel methodologies to improve existing machine learning models.\n\n* Minimum of 3 years of software development experience including coding, testing, troubleshooting, and deployment.\n\n* Minimum of 2 years experience with building production end-to-end machine learning models at scale.\n\n* Strong knowledge of machine learning frameworks.\n\n* Python programming proficiency.\n\n* SQL, MySQL or Postgres experience.\n\n* Strong desire to contribute to a rapidly growing startup and being comfortable with learning new tools and technologies.\n\n\n\n\n\nBonus points for knowledge of:\n\n\n* Real estate markets, MLS assessor/tax and parcel data.\n\n\n\n\n\nWhat we can offer you:\n\n\n* An amazing opportunity to be an integral part of building the next multi-billion dollar consumer brand around the single largest purchase of our lives.\n\n* Talented, passionate and mission-driven peers disrupting the status quo.\n\n* Competitive cash, full medical, dental, vision benefits, 401k, flexible work schedule, unlimited vacation (2 weeks mandatory) and sick time.\n\n* Flexibility to live and work anywhere within the United States. As we are a distributed company and engineering team, we are open to any U.S. location for this role.\n\n* This is a 100% remote, full-time career at Knock.\n\n\n\n\n\nWe have offices in New York, San Francisco, Atlanta, Charlotte, Raleigh, Dallas-Fort Worth, Phoenix, and Denver with more on the way. In fact, we are proud to be a distributed company with employees in 21 different states. This is an amazing opportunity to be an integral part of building a multi-billion dollar consumer brand in an industry that is long overdue for a new way of doing things. You will be working with a passionate, mission-driven team that is disrupting the status quo.\n\n\nKnock is an Equal Opportunity Employer.\n\n\nPlease no recruitment firm or agency inquiries, you will not receive a reply from us. \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Machine Learning, Senior and Engineer jobs that are similar:\n\n $70,000 — $130,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n

We're a well-funded team building open source tools for ML workflow. Our first and core project, [DVC](https://github.com/iterative/dvc), has excellent traction and positive feedback from community. Our mission as a company is to build tools for engineers and data scientists that they love to use.\n\n**Our culture/what we offer:**\n\n- Team is distributed remotely worldwide.\n- Highly competitive salary, stock options, and bonuses.\n- Open source.\n- Founders and team with strong engineering, data science, and open source experience. We all code and understand engineering first-hand.\n- Engineering team is involved into product discussions and planning. We do it openly via [Github](https://github.com/iterative/dvc) or Discord [chat](https://dvc.org/chat).\n- Besides building the product we participate in conferences (PyCon, PyData, O'Reilly AI, etc). We encourage and support the team in giving talks, writing blog-posts, etc.\n- Well-defined process that we all participate in improving.\n\n**Join us if you like us love building open source and developer tools!**\n\n# Responsibilities\n - Discuss and research issues, features, new products.\n- Write code (see some [PR examples](https://github.com/iterative/dvc/pulls?q=is%3Apr+is%3Aclosed) ).\n- Write docs if needed for your code (see this [repo](https://github.com/iterative/dvc.org )).\n- Being actively involved with the community - talk to users on Github, Discord, forum. \n\n# Requirements\nStrong Python knowledge and excellent coding culture (standards, unit test, etc) are required. Alternatively, strong skill in other languages along with some knowledge of Python is also acceptable.\n\n**Must have:**\n\n- Motivation and interest\n- Remote work self-discipline\n- Excellent communication skills - clear, constructive, and respectful dialog with other team members, community.\n- Can focus and deliver a task w/o constantly switching to other stuff - respect team's planning, deadlines, etc\n\n**Great to have:**\n\n- Experience working remotely\n- Open source contributions or experience of maintaining, developing an open source project\n- System programming experience - kernel, databases, etc.\n- Machine learning or data science experience \n\nPlease mention the words **OCCUR LOUD GLOVE** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4yNDM=). This is a feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.\n\n \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Python, Machine Learning, Data Science, Senior, Engineer, Developer and Digital Nomad jobs that are similar:\n\n $70,000 — $130,000/year\n \n\n#Location\nWorldwide

\nResearch Square is the leader in ethical author-oriented solutions in the world of academic publishing. We are home to American Journal Experts (AJE), which provides solutions that help researchers communicate their work so they can get back to making discoveries.\n\nWe currently have a challenging opportunity for a bright, hardworking, and self-motivated Machine Learning Engineer. We are looking for an early-career individual who exhibits personal humility and who strives to enable the success of their team in our fun and collaborative remote environment. A successful candidate will be excited to learn and stay abreast of new advancements in the field. \n\nAs a Machine Learning Engineer at Research Square, your efforts will support our engineering and operations teams across a variety of projects involving the creation of new tools and the support and improvement of existing tools. You will be responsible for all parts of model creation from data wrangling to model testing and validation.\n\n\nRequirements for this role include\n\n\n* Uses appropriate ML techniques and big data to create automation solutions for business-critical problems\n\n* Assesses and advocates for automation solutions based on their cost to implement and probability of success\n\n* Considers scalability, user experience, and biases in data when designing solutions\n\n* Experience with natural language processing or a strong desire to learn\n\n* Collaborates with business stakeholders to understand business objectives and develop models to help achieve them, along with metrics to track their effectiveness. \n\n* Works both strategically and tactically to achieve business outcomes\n\n* High level of comfort with Python, SQL, Git, and using the command line.\n\n* Works with complex structured and unstructured data, to include leading the data acquisition process, data cleaning, exploratory analysis, verification, and designing data pipelines. Validates models to ensure adequate real-world performance.\n\n* Bachelor’s degree or equivalent experience\n\n\n\n\nOur ideal candidate also has experience with the following: \n\n\n* One to two years experience in practical machine learning\n\n* Optimizing existing or new ML solutions for performance and scale\n\n* Demonstrated experience with deep learning\n\n* Natural Language Processing and/or Computational linguistics\n\n* Amazon Web Services and/or Google Cloud\n\n\n \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Machine Learning, Engineer, Developer and Digital Nomad jobs that are similar:\n\n $65,000 — $130,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n

\nSummary\n\nThe Wikimedia Foundation is growing its Machine learning efforts. This an opportunity to be part of the team that builds and maintain machine learning technologies to empower millions of users – readers, contributors, and donors – who contribute to Wikipedia and its sister projects on a daily basis. We address process inefficiencies with machine learning technologies, we design and test new technology, we produce empirical insights, and we publish and present research of the intersection of technology and culture. We are strongly committed to principles of transparency, privacy, and collaboration. We use free and open source technology and we collaborate with external researchers and our volunteer community.\n\nWe are looking for an experienced Engineering Manager to help build features that enable our communities to achieve our Vision: a world in which every single human being can freely share in the sum of all knowledge. As an Engineering Manager, you will support engineers building features, products, and services used by hundreds of millions of people around the world. This is an opportunity to do good while improving one of the best known sites in the world.\n\nWe’d like you to do these things:   \n\n\n* Partner closely with other teams and departments across the Wikimedia Foundation to define and experiment with machine learning products. These could be brand new feature offerings in Wikipedia or augmentation of existing workflows.\n\n* Review and advice in code changes made by team.\n\n* Represent team members within the organization and Wikimedia community.\n\n* Support and coach your team members in the development of their career paths.\n\n* Recruit and hire new team members.\n\n\n\n\nWe’d like you to have these skills: \n\n\n* Multiple years of experience in leading software engineering teams and managing complex projects.\n\n* Practical experience with machine learning, natural language processing or information retrieval in products that have been launched to production.\n\n* Excellent analytical and problem solving skills. Familiarity with statistics.\n\n* Significant experience working with data infrastructure and distributed systems at scale.\n\n* Experience with both scripting and compiled languages in a Linux/Unix server environment, some of: Python, PHP, Java, Javascript, C, Scala\n\n* Excellent verbal and written communication skills\n\n* BS in Computer Science or other relevant technical field or the equivalent in related work experience.\n\n\n\n\nAnd it would be even more awesome if you have this:\n\n\n* Previous experience working on a large, mature, open source project\n\n* Experience working with a geographically distributed software engineering team\n\n* Experience with open source software development\n\n* Contributing to the Wikipedia or Wikimedia project communities\n\n\n\n\nShow us your stuff! If you have any existing open source software that you or teams you have lead have  developed (these could be your own software or patches to other packages), please share the URLs for the source. Links to GitHub,GitLab, BitBucket, Presi, YouTube, Medium, etc. are especially useful.\n\nU.S. Benefits & Perks*\n\n\n* Fully paid medical, dental and vision coverage for employees and their eligible families (yes, fully paid premiums!)\n\n* The Wellness Program provides reimbursement for mind, body and soul activities such as fitness memberships, baby sitting, continuing education and much more\n\n* The 401(k) retirement plan offers matched contributions at 4% of annual salary\n\n* Flexible and generous time off - vacation, sick and volunteer days, plus 19 paid holidays - including the last week of the year.\n\n* Family friendly! 100% paid new parent leave for seven weeks plus an additional five weeks for pregnancy, flexible options to phase back in after leave, fully equipped lactation room.\n\n* For those emergency moments - long and short term disability, life insurance (2x salary) and an employee assistance program\n\n* Pre-tax savings plans for health care, child care, elder care, public transportation and parking expenses\n\n* Telecommuting and flexible work schedules available\n\n* Appropriate fuel for thinking and coding (aka, a pantry full of treats) and monthly massages to help staff relax\n\n* Great colleagues - diverse staff and contractors speaking dozens of languages from around the world, fantastic intellectual discourse, mission-driven and intensely passionate people\n\n\n\n\n*Eligible international workers' benefits are specific to their location and dependent on their employer of record\n\nMore information\n\nWMF\nBlog\nWikimedia 2030\nWikimedia Medium Term Plan\nDiversity and inclusion information for Wikimedia workers, by the numbers\nWikimania 2019\nAnnual Report - 2017 \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Machine Learning, Engineer and Executive jobs that are similar:\n\n $80,000 — $120,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n

\nSummary\n\nThe Wikimedia Foundation is growing its Machine learning efforts. This an opportunity to be part of the team that builds and maintain machine learning technologies to empower millions of users – readers, contributors, and donors – who contribute to Wikipedia and its sister projects on a daily basis. We address process inefficiencies with machine learning technologies, we design and test new technology, we produce empirical insights, and we publish and present research of the intersection of technology and culture. We are strongly committed to principles of transparency, privacy, and collaboration. We use free and open source technology and we collaborate with external researchers and our volunteer community.\n\nWe are looking for an experienced Engineering Manager to help build features that enable our communities to achieve our Vision: a world in which every single human being can freely share in the sum of all knowledge. As an Engineering Manager, you will support engineers building features, products, and services used by hundreds of millions of people around the world. This is an opportunity to do good while improving one of the best known sites in the world.\n\nWe’d like you to do these things:   \n\n\n* Partner closely with other teams and departments across the Wikimedia Foundation to define and experiment with machine learning products. These could be brand new feature offerings in Wikipedia or augmentation of existing workflows.\n\n* Review and advice in code changes made by team.\n\n* Represent team members within the organization and Wikimedia community.\n\n* Support and coach your team members in the development of their career paths.\n\n* Recruit and hire new team members.\n\n\n\n\nWe’d like you to have these skills: \n\n\n* Multiple years of experience in leading software engineering teams and managing complex projects.\n\n* Practical experience with machine learning, natural language processing or information retrieval in products that have been launched to production.\n\n* Excellent analytical and problem solving skills. Familiarity with statistics.\n\n* Significant experience working with data infrastructure and distributed systems at scale.\n\n* Experience with both scripting and compiled languages in a Linux/Unix server environment, some of: Python, PHP, Java, Javascript, C, Scala\n\n* Excellent verbal and written communication skills\n\n* BS in Computer Science or other relevant technical field or the equivalent in related work experience.\n\n\n\n\nAnd it would be even more awesome if you have this:\n\n\n* Previous experience working on a large, mature, open source project\n\n* Experience working with a geographically distributed software engineering team\n\n* Experience with open source software development\n\n* Contributing to the Wikipedia or Wikimedia project communities\n\n\n\n\nShow us your stuff! If you have any existing open source software that you or teams you have lead have  developed (these could be your own software or patches to other packages), please share the URLs for the source. Links to GitHub,GitLab, BitBucket, Presi, YouTube, Medium, etc. are especially useful.\n\n\n\nU.S. Benefits & Perks*\n\n\n* Fully paid medical, dental and vision coverage for employees and their eligible families (yes, fully paid premiums!)\n\n* The Wellness Program provides reimbursement for mind, body and soul activities such as fitness memberships, baby sitting, continuing education and much more\n\n* The 401(k) retirement plan offers matched contributions at 4% of annual salary\n\n* Flexible and generous time off - vacation, sick and volunteer days, plus 19 paid holidays - including the last week of the year.\n\n* Family friendly! 100% paid new parent leave for seven weeks plus an additional five weeks for pregnancy, flexible options to phase back in after leave, fully equipped lactation room.\n\n* For those emergency moments - long and short term disability, life insurance (2x salary) and an employee assistance program\n\n* Pre-tax savings plans for health care, child care, elder care, public transportation and parking expenses\n\n* Telecommuting and flexible work schedules available\n\n* Appropriate fuel for thinking and coding (aka, a pantry full of treats) and monthly massages to help staff relax\n\n* Great colleagues - diverse staff and contractors speaking dozens of languages from around the world, fantastic intellectual discourse, mission-driven and intensely passionate people\n\n\n\n\n*Eligible international workers' benefits are specific to their location and dependent on their employer of record\n\nMore information\n\nWMF\nBlog\nWikimedia 2030\nWikimedia Medium Term Plan\nDiversity and inclusion information for Wikimedia workers, by the numbers\nWikimania 2019\nAnnual Report - 2017 \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Machine Learning, Engineer and Executive jobs that are similar:\n\n $80,000 — $120,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n

\nSummary\n\nThe Wikimedia Foundation is growing its Machine learning efforts. This an opportunity to be part of the team that builds and maintain machine learning technologies to empower millions of users – readers, contributors, and donors – who contribute to Wikipedia and its sister projects on a daily basis. We address process inefficiencies with machine learning technologies, we design and test new technology, we produce empirical insights, and we publish and present research of the intersection of technology and culture. We are strongly committed to principles of transparency, privacy, and collaboration. We use free and open source technology and we collaborate with external researchers and our volunteer community.\n\nWe are looking for an experienced Engineering Manager to help build features that enable our communities to achieve our Vision: a world in which every single human being can freely share in the sum of all knowledge. As an Engineering Manager, you will support engineers building features, products, and services used by hundreds of millions of people around the world. This is an opportunity to do good while improving one of the best known sites in the world.\n\nWe’d like you to do these things:   \n\n\n* Partner closely with other teams and departments across the Wikimedia Foundation to define and experiment with machine learning products. These could be brand new feature offerings in Wikipedia or augmentation of existing workflows.\n\n* Review and advice in code changes made by team.\n\n* Represent team members within the organization and Wikimedia community.\n\n* Support and coach your team members in the development of their career paths.\n\n* Recruit and hire new team members.\n\n\n\n\nWe’d like you to have these skills: \n\n\n* Multiple years of experience in leading software engineering teams and managing complex projects.\n\n* Practical experience with machine learning, natural language processing or information retrieval in products that have been launched to production.\n\n* Excellent analytical and problem solving skills. Familiarity with statistics.\n\n* Significant experience working with data infrastructure and distributed systems at scale.\n\n* Experience with both scripting and compiled languages in a Linux/Unix server environment, some of: Python, PHP, Java, Javascript, C, Scala\n\n* Excellent verbal and written communication skills\n\n* BS in Computer Science or other relevant technical field or the equivalent in related work experience.\n\n\n\n\nAnd it would be even more awesome if you have this:\n\n\n* Previous experience working on a large, mature, open source project\n\n* Experience working with a geographically distributed software engineering team\n\n* Experience with open source software development\n\n* Contributing to the Wikipedia or Wikimedia project communities\n\n\n\n\nShow us your stuff! If you have any existing open source software that you or teams you have lead have  developed (these could be your own software or patches to other packages), please share the URLs for the source. Links to GitHub,GitLab, BitBucket, Presi, YouTube, Medium, etc. are especially useful.\n\nThe Wikimedia Foundation is... \n\n\n...the nonprofit organization that hosts and operates Wikipedia and the other Wikimedia free knowledge projects. Our vision is a world in which every single human can freely share in the sum of all knowledge. We believe that everyone has the potential to contribute something to our shared knowledge, and that everyone should be able to access that knowledge, free of interference. We host the Wikimedia projects, build software experiences for reading, contributing, and sharing Wikimedia content, support the volunteer communities and partners who make Wikimedia possible, and advocate for policies that enable Wikimedia and free knowledge to thrive. The Wikimedia Foundation is a charitable, not-for-profit organization that relies on donations. We receive financial support from millions of individuals around the world, with an average donation of about $15. We also receive donations through institutional grants and gifts. The Wikimedia Foundation is a United States 501(c)(3) tax-exempt organization with offices in San Francisco, California, USA.\n\nThe Wikimedia Foundation is an equal opportunity employer, and we encourage people with a diverse range of backgrounds to apply\n\n\nU.S. Benefits & Perks*\n\n\n* Fully paid medical, dental and vision coverage for employees and their eligible families (yes, fully paid premiums!)\n\n* The Wellness Program provides reimbursement for mind, body and soul activities such as fitness memberships, baby sitting, continuing education and much more\n\n* The 401(k) retirement plan offers matched contributions at 4% of annual salary\n\n* Flexible and generous time off - vacation, sick and volunteer days, plus 19 paid holidays - including the last week of the year.\n\n* Family friendly! 100% paid new parent leave for seven weeks plus an additional five weeks for pregnancy, flexible options to phase back in after leave, fully equipped lactation room.\n\n* For those emergency moments - long and short term disability, life insurance (2x salary) and an employee assistance program\n\n* Pre-tax savings plans for health care, child care, elder care, public transportation and parking expenses\n\n* Telecommuting and flexible work schedules available\n\n* Appropriate fuel for thinking and coding (aka, a pantry full of treats) and monthly massages to help staff relax\n\n* Great colleagues - diverse staff and contractors speaking dozens of languages from around the world, fantastic intellectual discourse, mission-driven and intensely passionate people\n\n\n\n\n*Eligible international workers' benefits are specific to their location and dependent on their employer of record\n\nMore information\n\nWikimedia Foundation website\n\nWikimedia Foundation blog\n\nAnnual Report - 2017\n\nWikimedia 2030 \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Machine Learning, Engineer and Executive jobs that are similar:\n\n $80,000 — $120,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n

\nAre you inspired by innovation, hard work and a passion for data?    \n\nIf so, this may be the ideal opportunity to leverage your Software Engineering, Data Engineering or Data Analytics experience to design, develop and innovate big data solutions for a diverse set of clients.  \n\nAt phData, our proven success has skyrocketed the demand for our services, resulting in quality growth and an expanded presence at our company headquarters conveniently located in Downtown Minneapolis (Fueled Collective).\n\nAs the world’s largest pure-play Big Data, Machine Learning and Data Science services firm, our team includes Apache committers, Machine Learning experts and the most knowledgeable Scala development team in the industry. phData has earned the trust of customers by demonstrating our mastery of Big Data and Machine Learning services and our commitment to excellence.\n\nIn addition to a phenomenal growth and learning opportunity, we offer competitive compensation and excellent perks including base salary, annual bonus, extensive training, paid Cloudera certifications - in addition to generous PTO and employee equity.\n\nAs a Machine Learning Engineer, your responsibilities include: \n\n\n\n\n* Convert proof of concepts to production-grade solutions that can scale for hundreds of thousands of users\n\n\n\n* Create and manage machine learning pipelines on a Hadoop cluster to support any kind of model deployment on streaming or batch data.\n\n\n\n* Tackle challenging problems, such as developing web services and ETL pipeline components, to productize and evaluate machine learning models\n\n\n\n* Write production code and collaborate with Solutions Architects and Data Scientists to implement algorithms in production\n\n\n\n* Design, conduct, and analyze experiments to validate proposed ML modeling approaches as well as improvements to existing ML pipelines\n\n\n\n\n\n\nQualifications\n\n\n* Previous experience as a Software Engineer, Data Engineer or Data Scientist (with hands-on engineering experience)\n\n* Solid programming experience in Python, Java, Scala, or other statically typed programming language\n\n* Hands-on experience in one or more big data ecosystem products/languages such as Spark, Impala, Solr, Kudu, etc\n\n* Experience working with Data Science/Machine Learning software and libraries such as h2o, TensorFlow, Keras, scikit-learn, etc.\n\n* Strong working knowledge of SQL and the ability to write, debug, and optimize distributed SQL queries\n\n* Excellent communication skills; previous experience working with internal or external customers\n\n* Strong analytical abilities; ability to translate business requirements and use cases into a Hadoop solution, including ingestion of many data sources, ETL processing, data access, and consumption, as well as custom analytics\n\n* 4 year Bachelor's Degree in Computer Science or a related field, or equivalent years of professional working experience.\n\n\n\n\nKeywords: Hive, Apache Spark, Java, Apache Kafka, Big Data, Spark, Solution Architecture, Cloudera, Apache Pig, Hadoop, NoSQL, Cloudera Impala, Scala, Python, Data Engineering, Big Data Analytics, Large Scale Data Analysis, ETL, Linux, Kudu, Pandas, TensorFlow, h2o, R, Keras, PyTorch, scikit-learn, Machine Learning, Machine Learning Engineering, Data Science, PySpark, NLP \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Machine Learning, Engineer, Scala and Apache jobs that are similar:\n\n $80,000 — $130,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n

\nSummary\n\nThe Wikimedia Foundation is growing its Machine learning efforts. This an opportunity to be part of the team that builds and maintain machine learning technologies to empower millions of users – readers, contributors, and donors – who contribute to Wikipedia and its sister projects on a daily basis. We address process inefficiencies with machine learning technologies, we design and test new technology, we produce empirical insights, and we publish and present research of the intersection of technology and culture. We are strongly committed to principles of transparency, privacy, and collaboration. We use free and open source technology and we collaborate with external researchers and our volunteer community.\n\nWe are looking for an experienced Engineering Manager to help build features that enable our communities to achieve our Vision: a world in which every single human being can freely share in the sum of all knowledge. As an Engineering Manager, you will support engineers building features, products, and services used by hundreds of millions of people around the world. This is an opportunity to do good while improving one of the best known sites in the world.\n\nWe’d like you to do these things:   \n\n\n* Partner closely with other teams and departments across the Wikimedia Foundation to define and experiment with machine learning products. These could be brand new feature offerings in Wikipedia or augmentation of existing workflows.\n\n* Review and advice in code changes made by team.\n\n* Represent team members within the organization and Wikimedia community.\n\n* Support and coach your team members in the development of their career paths.\n\n* Recruit and hire new team members.\n\n\n\n\nWe’d like you to have these skills: \n\n\n* Multiple years of experience in leading software engineering teams and managing complex projects.\n\n* Practical experience with machine learning, natural language processing or information retrieval in products that have been launched to production.\n\n* Excellent analytical and problem solving skills. Familiarity with statistics.\n\n* Significant experience working with data infrastructure and distributed systems at scale.\n\n* Experience with both scripting and compiled languages in a Linux/Unix server environment, some of: Python, PHP, Java, Javascript, C, Scala\n\n* Excellent verbal and written communication skills\n\n* BS in Computer Science or other relevant technical field or the equivalent in related work experience.\n\n\n\n\nAnd it would be even more awesome if you have this:\n\n\n* Previous experience working on a large, mature, open source project\n\n* Experience working with a geographically distributed software engineering team\n\n* Experience with open source software development\n\n* Contributing to the Wikipedia or Wikimedia project communities\n\n\n\n\nShow us your stuff! If you have any existing open source software that you or teams you have lead have  developed (these could be your own software or patches to other packages), please share the URLs for the source. Links to GitHub,GitLab, BitBucket, Presi, YouTube, Medium, etc. are especially useful.\n\nThe Wikimedia Foundation is... \n\n\n...the nonprofit organization that hosts and operates Wikipedia and the other Wikimedia free knowledge projects. Our vision is a world in which every single human can freely share in the sum of all knowledge. We believe that everyone has the potential to contribute something to our shared knowledge, and that everyone should be able to access that knowledge, free of interference. We host the Wikimedia projects, build software experiences for reading, contributing, and sharing Wikimedia content, support the volunteer communities and partners who make Wikimedia possible, and advocate for policies that enable Wikimedia and free knowledge to thrive. The Wikimedia Foundation is a charitable, not-for-profit organization that relies on donations. We receive financial support from millions of individuals around the world, with an average donation of about $15. We also receive donations through institutional grants and gifts. The Wikimedia Foundation is a United States 501(c)(3) tax-exempt organization with offices in San Francisco, California, USA.\n\nThe Wikimedia Foundation is an equal opportunity employer, and we encourage people with a diverse range of backgrounds to apply\n\n\nU.S. Benefits & Perks*\n\n\n* Fully paid medical, dental and vision coverage for employees and their eligible families (yes, fully paid premiums!)\n\n* The Wellness Program provides reimbursement for mind, body and soul activities such as fitness memberships, baby sitting, continuing education and much more\n\n* The 401(k) retirement plan offers matched contributions at 4% of annual salary\n\n* Flexible and generous time off - vacation, sick and volunteer days, plus 19 paid holidays - including the last week of the year.\n\n* Family friendly! 100% paid new parent leave for seven weeks plus an additional five weeks for pregnancy, flexible options to phase back in after leave, fully equipped lactation room.\n\n* For those emergency moments - long and short term disability, life insurance (2x salary) and an employee assistance program\n\n* Pre-tax savings plans for health care, child care, elder care, public transportation and parking expenses\n\n* Telecommuting and flexible work schedules available\n\n* Appropriate fuel for thinking and coding (aka, a pantry full of treats) and monthly massages to help staff relax\n\n* Great colleagues - diverse staff and contractors speaking dozens of languages from around the world, fantastic intellectual discourse, mission-driven and intensely passionate people\n\n\n\n\n*Eligible international workers' benefits are specific to their location and dependent on their employer of record\n\nMore information\n\nWikimedia Foundation website\n\nWikimedia Foundation blog\n\nAnnual Report - 2017\n\nWikimedia 2030 \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Machine Learning, Engineer and Executive jobs that are similar:\n\n $80,000 — $120,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n