**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 (#RMjE2LjczLjIxNi4yMjQ=). 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 (#RMjE2LjczLjIxNi4yMjQ=). 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 (#RMjE2LjczLjIxNi4yMjQ=). 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

**Company Description**\n\nShopify is now permanently remote and working towards a future that is digital by default. Learn more about what this can mean for you.\n\nAt Shopify, we build products that help entrepreneurs around the world start and grow their business. We’re the world’s fastest growing commerce platform with over 1 million merchants in more than 175 different countries, with solutions from point-of-sale and online commerce to financial, shipping logistics and marketing.\n\n**Job Description**\n\nData is a crucial part of Shopify’s mission to make commerce better for everyone. We organize and interpret petabytes of data to provide solutions for our merchants and stakeholders across the organization. From pipelines and schema design to machine learning products and decision support, data science at Shopify is a diverse role with many opportunities to positively impact our success. \n\nOur Data Scientists focus on pushing products and the business forward, with a focus on solving important problems rather than specific tools. We are looking for talented data scientists to help us better understand our merchants and buyers so we can help them on their journey.\n\n**Responsibilities:**\n\n* Proactively identify and champion projects that solve complex problems across multiple domains\n* Partner closely with product, engineering and other business leaders to influence product and program decisions with data\n* Apply specialized skills and fundamental data science methods (e.g. regression, survival analysis, segmentation, experimentation, and machine learning when needed) to inform improvements to our business\n* Design and implement end-to-end data pipelines: work closely with stakeholders to build instrumentation and define dimensional models, tables or schemas that support business processes\n* Build actionable KPIs, production-quality dashboards, informative deep dives, and scalable data products\n* Influence leadership to drive more data-informed decisions\n* Define and advance best practices within data science and product teams\n\n**Qualifications**\n\n* 4-6 years of commercial experience as a Data Scientist solving high impact business problems\n* Extensive experience with Python and software engineering fundamentals\n* Experience with applied statistics and quantitative modelling (e.g. regression, survival analysis, segmentation, experimentation, and machine learning when needed)\n* Demonstrated ability to translate analytical insights into clear recommendations and effectively communicate them to technical and non-technical stakeholders\n* Curiosity about the problem domain and an analytical approach\n* Strong sense of ownership and growth mindset\n \n**Experience with one or more:**\n\n* Deep understanding of advanced SQL techniques\n* Expertise with statistical techniques and their applications in business\n* Masterful data storytelling and strategic thinking\n* Deep understanding of dimensional modelling and scaling ETL pipelines\n* Experience launching productionized machine learning models at scale\n* Extensive domain experience in e-commerce, marketing or SaaS\n\n**Additional information**\n\nAt Shopify, we are committed to building and fostering an environment where our employees feel included, valued, and heard. Our belief is that a strong commitment to diversity and inclusion enables us to truly make commerce better for everyone. We strongly encourage applications from Indigenous people, racialized people, people with disabilities, people from gender and sexually diverse communities and/or people with intersectional identities. Please take a look at our 2019 Sustainability Report to learn more about Shopify's commitments. \n\nPlease mention the words **STOVE SIEGE FRESH** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4yMjQ=). 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\nUnited States, Canada

# About the Role\n\nWe are looking for a Senior Data Scientist to help us prototype and implement AI monitoring systems. You will work along with a team of experienced Data Scientists, Data Engineers and Software Engineers. You will be responsible for implementing AI monitoring algorithms. As we grow NannyML, we expect you to grow with us. We envision your path may grow from your position into ML Engineering Team Lead. You will get meaningfully involved in the areas of product, engineering, hiring and people management among others.\n\n## Responsibilities\n\n* Research, prototype and implement Drift Detection algorithms, time-series anomaly detection, and other ML monitoring algorithms.\n* Tackle new research and ML problems and implement efficient and effective solutions.\n* Take part in customer meetings and help with client on-boarding to fully understand and fulfill their needs.\n* Help design and develop new internal tools to facilitate product development and algorithmic research.\n* Work closely with the founding to help define the technical roadmap.\n\n# About Us\n\nNannyML is an early stage [venture funded](https://www.eu-startups.com/2020/10/belgian-ai-monitoring-startup-nannyml-secures-e1-million-to-bridge-the-gap-between-ai-and-business/) 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 and 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 we extract 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## Our values\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. You will be working closely with the founding team. The team previously founded a specialized machine learning company, where they became experts at building machine learning systems.\n\n# Basic Requirements\n\n* Ignore everything below (including the compensation) if you have significant hands-on experience in AI monitoring\n* 3+ years of previous experience developing production ready Machine Learning models on tabular or time-series data\n* Deep understanding of statistical methods and modern ML algorithms and experience evaluating the suitability of various approaches for a use case\n* Strong experience in Python data stack and ML deployment technologies\n* Software engineering best practices, version control, containerization and testing\n* Exceptional 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* You live in or are willing and able to relocate to EU time zones and you are open to travel occasionally\n\n## Nice to haves\n\n* ML publications, popular technical blog or significant open source contributions\n* Familiarity with model risk management, model monitoring or model maintenance\n* Masters or PhD degree in a STEM related field\n* Experience working at a data-focused startup\n\n# Benefits\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* Compensation: up to 85,000 EUR/year + equity \n\nPlease mention the words **COYOTE STAMP VIOLIN** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4yMjQ=). 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 $60,000 — $100,000/year\n \n\n#Location\nEurope

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 (#RMjE2LjczLjIxNi4yMjQ=). 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 (#RMjE2LjczLjIxNi4yMjQ=). 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)

\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

\nThe Machine Learning Specialist advances Advent Health Partners’ machine learning strategy.\nAdvent has a number of tools designed to display and gather data. This data has deeper\nmeaning and it is our goal as a company to build a machine learning architecture to maximize\nthe interpretation of this data in order to develop reliable predictive models\n\nEssential Duties and Responsibilities\n Communicate effectively with executive and clinical personnel\n Identify trends and relationships in the data used for creating and testing hypotheses.\n Mine and analyze structured/unstructured data to create algorithms\n Identify information-rich features in large target datasets\n Formulate innovative solutions to problems where machine learning is applicable\n Collaborate with Principal Scientist, Product Manager, Senior Application Developer and\nVP Engineering to produce the best possible end product\n Recommend a scalable, reliable hardware/software/saas platform\n Maintain discussions of proposed features as Github Issues\n Tweak and debug in collaboration with peers\n Maintain Slack conversations during working hours\n Provide work effort estimates to management to assist in setting priorities\n Deliver timely work in accordance with estimates\n Solve problems as they arise and communicate potential roadblocks to manage\nexpectations\n Adhere strictly to all security policies.\n\nMinimum Qualifications (Knowledge, Skills, and Abilities)\n Advanced Degree in a quantitative field such as Computer Science, Physics, Statistics,\nor related fields is preferred\n 2+ years in machine learning post-doc or professional\n Demonstrated experience working with both structured and unstructured data\n Demonstrated experience in identifying information-rich features and/or strategies for\nidentifying information-rich features in large datasets\n\n Knowledge of a variety of machine learning techniques (clustering, classification,\nregression, neural networks, etc.) and their real-world advantages/drawbacks\n Strong programming skills in Python and relevant ML libraries such as scikit-lern,\nTensorFLow and PyTorch.\n Experience in using NLP modules within Python\n Familiar with OCR modules within Python\n Experience in healthcare industry is a plus\n Experience in applying core Machine Learning methodologies: Regression, Naive\nBayesian classifier, Clustering, Matrix Factorization, k-Nearest Neighbors, Natural\nLanguage processing, Decision trees, Support Vector Machines, Neural Networks/ Deep\nLearning, Convolution Neural Networks\n Experience with AWS\n Proficient in REST, JSON\n Understanding of unit testing\n Strong written and verbal communication skills\n An experienced grasp of version control, branches and git in particular\n Thorough understanding of working in development, staging and production\nenvironments\n Unix-related skills including installation with apt-get, compiling from source, intermediate\nshell scripting \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Machine Learning, Git, Python, Senior, Medical and Non Tech jobs that are similar:\n\n $70,000 — $127,500/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 (#RMjE2LjczLjIxNi4yMjQ=). 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

\nWe are looking for an experienced Machine Learning Engineer to help us build-out artificial intelligence capabilities into our existing line of cloud product services.  You will be responsible for developing software components for our products to utilize machine learning for the recognition of document image data, forms and handwriting.  Your ultimate goal will be to shape and build efficient self-learning application subsystems to eliminate the need for human processing.  \n\nResponsibilities Include:\n\n\n* Software architecture, design and implementation\n\n* Train & Validate TensorFlow Models for Hand Written Text Recognition\n\n* Deploy TensorFlow Models in Azure cloud that support multi-threading\n\n* Build a service (API) to access deployed model in Azure and validate image text\n\n* Create an automated schedule to daily train model with new data to improve accuracy\n\n* Build multiple versions of TensorFlow Model based on accuracy improvement and deploy improved model version to Azure cloud\n\n\n\n\nQualifications:\n\n\n* Bachelor degree in Computer Science / Engineering and 10+ years of software development experience\n\n* Proven experience with Machine learning technologies such as TensorFlow\n\n* Experience with Python, Python Packages, OpenCV and Keras\n\n* Experience with Microsoft Azure\n\n* U.S. citizenship required\n\n* Must pass a security background check.\n\n\n\n\nRequired skills:\n\n\n* Commercial application development experience\n\n* Ability to write robust code in Python, Java and C#\n\n* RESTful Web Service development\n\n* Must be able to work independently and remotely\n\n* Must be detail oriented with good oral and written communication skills\n\n\n\n\nThis position has possible option in future to hire into a full time permanent position. \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, Developer, Digital Nomad, Java, Cloud, Python, Microsoft 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

\n Thrive Global is changing the way people live through our behavior change platform and apps used to impact individual and organizational well-being and productivity. The marriage of data and analytics, our best-in-class content and science-backed behavior change IP will help people go from knowing what to do to actually doing it, enabling millions of consumers to begin the Thrive behavior change journey.  As a technical lead on Thrive’s Data Science and Analytics team, you will play a significant role in building Thrive’s platform and products.\n\nWho We Are Looking For\n\n\n* A versatile engineering lead who has significant experience with data at all levels of maturity:  raw telemetry through deployment and maintenance of models in operations \n\n* Is excited about collaborating with others, engineering and non-engineering, both learning & teaching as Thrive grows.\n\n* An innovator looking to push the boundaries of automation, intelligent ETL, AIOps and MlOps to drive high-quality insights and operational efficiency within the team\n\n* Has a proven track record of building and shipping data-centric software products\n\n* Desires a position that is approximately 75% individual technical contributions and 25% mentoring junior engineers or serving as a trusted advisor to engineering leadership\n\n* Is comfortable in a high growth, start-up environment and is willing to wear many hats and come up with creative solutions.\n\n\n\n\nHow You’ll Contribute\n\n\n* Collaborate with the Head of Data Science and Analytics to design an architecture and infrastructure to support data engineering and machine learning at Thrive\n\n* Implement a production-grade data science platform which includes building data pipeline, automation of data quality assessments, and automatic deployment of models into production\n\n* Develop new technology solutions to ensure a seamless transition of machine learning algorithms to production software, to enable the building out of easy to use datasets and to reduce other friction points within the data science life-cycle\n\n* Assist with building a small but skilled interdisciplinary team of data professionals: scientists, analysts, and engineers\n\n* Consider user privacy and security at all times\n\n\n\n\nRequired Skills\n\n\n* Master’s or Ph.D. degree in Computer Science or a related discipline (e.g., Mathematics, Physics)\n\n* 3+ years of technical leadership, team size of 5 or more, in data engineering or machine learning projects\n\n* 8+ years of industry experience with data engineering and machine learning\n\n* Extensive programming experience in Java or Python with applications in data engineering and machine learning.\n\n* Experience with data modeling, large-scale batch, and real-time data processing, ETL design, implementation and maintenance\n\n* Excellent verbal and written communication skills\n\n* Self-starter with a positive attitude, intellectual curiosity and a passion for analytics and solving real-world problems\n\n\n\n\nRelevant Technology and Tools Experience\nA good cross-section of experience in the following areas is desired:\n\n\n* AI/ML platforms:  TensorFlow, Apache MXnet, Theano, Keras, CNTK, scikit-learn, H2O, Spark MLlib, AWS SageMaker, etc.\n\n* Relational databases: MySQL, Postgres, RedShift, etc.\n\n* Big data technologies:  Spark, HDFS, Hive, Yarn, etc.\n\n* Data ingestion tools: Kafka, NiFi, Storm, Amazon Kinesis, etc.\n\n* Deployment technologies:  Docker, Kubernetes, or OpenStack\n\n* Public Cloud:  Azure, AWS or Google Cloud Platform\n\n\n\n\nOur Mission\nThrive Global’s mission is to end the stress and burnout epidemic by offering companies and individuals sustainable, science-based solutions to enhance well-being, performance, and purpose, and create a healthier relationship with technology. Recent science has shown that the pervasive belief that burnout is the price we must pay for success is a delusion. We know, instead, that when we prioritize our well-being, our decision-making, creativity, and productivity improve dramatically. Thrive Global is committed to accelerating the culture shift that allows people to reclaim their lives and move from merely surviving to thriving.\n\nWhat We Offer\n\n\n* A mission-driven company that’s truly making a difference in the lives of people around the world  \n\n* Ability to develop within the company and shape our growth strategy\n\n* Human-centric culture with a range of wellness perks and benefits\n\n* Competitive compensation package\n\n* Medical, vision and dental coverage + 401k program with company match\n\n* Generous paid time-off programs \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, Executive, Teaching, Amazon, Java, Cloud, Python, Junior and Apache jobs that are similar:\n\n $75,000 — $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

\nData Science and Big Data are all we do.\n\nIf you're inspired by innovation and passionate about driving customer success - this may be the ideal opportunity to leverage your systems engineering and automation experience to build and support Machine Learning platforms for the clients we serve.\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 located in downtown Minneapolis and in Bangalore, India.\n\nAs the world’s first and only Data Science Enablement services firm and the largest pure-play Big Data service provider, our team includes Apache committers, Machine Learning experts and the most knowledgeable Spark and Scala development team in the industry. phData has earned the trust of customers by demonstrating our mastery of Data Science and Big Data services along with our commitment to excellence.\n\nIn addition to phenomenal growth and learning opportunities, we offer competitive compensation and excellent perks including base salary, annual bonus, extensive training, paid certifications - in addition to generous PTO, a comprehensive benefits program and employee equity.\n\nMachine Learning Platform Architect\n\nAs a Machine Learning Platform Architect, you will serve as the guiding force in architecting and engineering Machine Learning platforms for enterprise clients. In this hands-on role, your responsibilities will include:\n\n\n* Help automate and deploy Machine Learning platforms and applications\n\n* Guide customers on the best practices of upgrades, patches, and maintenance\n\n* Deploy continuous integration and security\n\n* Maintain constant curiosity and a thirst for learning\n\n* Investigate product related issues both for individual customers and for common trends that may arise\n\n* Participate in occasional weekend on-call rotation for critical support needs\n\n* Provide a best-in-class customer experience\n\n\n\n\nRequired Experience:\n\n\n* 5-7 years of Linux Systems Engineering experience to include monitoring, patches, upgrades, and O/S support\n\n* Proven system/application automation and deployment experience using Ansible, Chef, Puppet or similar tools\n\n* Experience with Application Web Frameworks is a plus;  Apache, Engenix, Tomcat, Spring, Flask, Play, etc is plus\n\n* Previous Consulting experience with external customers is highly preferred\n\n* Hands-on configuration with Security including LDAP, Active Directory\n\n* Passion for providing a great customer experience\n\n* Ability to work in a fast paced and agile environment\n\n* Excellent communication skills (written and verbal)\n\n* Strong problem-solving and analytical skills\n\n* Demonstrable troubleshooting skills\n\n* A positive attitude toward feedback and continual improvement\n\n\n\n\nPreferred Qualifications:\n\n\n* Working knowledge and experience with Python related technologies.\n\n* Understanding of networking, distributed systems, and Linux operating system concepts\n\n* Knowledge of relational database management systems (RDBMS), SQL and database concepts\n\n* On-the-job experience troubleshooting enterprise customer issues\n\n* Knowledge and experience with Kubernetes\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, Architecture, Python, Scala, Apache and Linux jobs that are similar:\n\n $80,000 — $125,000/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

Doximity is transforming the healthcare industry. Our mission is to help doctors save time so they can provide better care for patients.\n\nWe value diversity — in backgrounds and in experiences. Healthcare is a universal concern, and we need people from all backgrounds to help build the future of healthcare. Our data science team is deliberate and self-reflective about the kind of data team and culture that we are building, seeking data scientists and engineers that are not only strong in their own aptitudes but care deeply about supporting each other's growth. We have one of the richest healthcare datasets in the world, and our team brings a diverse set of technical and cultural backgrounds.\n\nDoximity’s social network has over 70% of US doctors as members. We recently launched a newsfeed which helps physicians navigate the latest practice-changing medical literature, parsing through millions of scientific studies while personalizing content to their patient base and every stage of their medical career. We’re looking for a deep learning expert to help our data science and engineering teams build models in support of the newsfeed, combining metadata from our clinician social graph with text-based features.\n\nHow you’ll make an impact:\n\n-Apply NLP methods and build deep neural networks to personalize medical content to our clinician -members.\n-Optimize the layout of different content types (e.g., journal articles, news articles, video, social updates) within the newsfeed.\n-Collaborate with data engineers to devise plans to refresh the newsfeed and surface optimized content to users near real-time.\n-Provide technical leadership to other data scientists and data engineers working on the newsfeed product.\n\nWhat we’re looking for:\n\n-4+ years of industry experience and M.S./Ph.D. in Computer Science, Engineering, Statistics, or other relevant technical field.\n-4+ years experience with various machine learning methods (classification, clustering, natural language processing, ensemble methods) and parameters that affect their performance.\n-Experience building deep neural networks in support of recommendation systems.\n-Solid engineering skills to build scalable solutions and help automate data processing challenges.\n-Desire to provide technical leadership and mentorship to other data team members.\n-Expert knowledge of probability and statistics (e.g., experimental design, optimization, predictive modeling).\n-Excellent problem-solving skills and ability to connect data science work to product impacts.\n-Fluent in SQL and Python; experience using Apache Spark (pyspark).\n-Experience working with relational and non-relational databases.\n\nNice to have:\n\n-Experience applying reinforcement learning to industry problems.\n\nAbout Doximity\n\nWe’re thrilled to be named the Fastest Growing Company in the Bay Area, and one of Fast Company’s Most Innovative Companies. Joining Doximity means being part of an incredibly talented and humble team. We work on amazing products that over 70% of US doctors (and over one million healthcare professionals) use to make their busy lives a little easier. We’re driven by the goal of improving inefficiencies in our $2.5 trillion U.S. healthcare system and love creating technology that has a real, meaningful impact on people’s lives. To learn more about our team, culture, and users, check out our careers page, company blog, and engineering blog. We’re growing fast, and there’s plenty of opportunity for you to make an impact—join us!\n\nDoximity is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. \n\nPlease mention the words **TRIM MUFFIN LIGHT** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4yMjQ=). 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, Medical and Apache jobs that are similar:\n\n $80,000 — $127,500/year\n

Doximity is transforming the healthcare industry. Our mission is to help doctors save time so they can provide better care for patients.\n\nWe value diversity — in backgrounds and in experiences. Healthcare is a universal concern, and we need people from all backgrounds to help build the future of healthcare.\n\nHow you’ll make an impact:\n\n-Employ appropriate methods to develop performant machine learning models at scale, owning them from inception to business impact.\n-Plan, engineer, and deploy both batch-processed and real-time data science solutions to increase user engagement with Doximity’s products.\n-Collaborate cross-functionally with data engineers and software engineers to architect and implement infrastructure in support of Doximity’s data science platform.\n-Improve the accuracy, runtime, scalability and reliability of machine intelligence systems\n-Think creatively and outside of the box. The ability to formulate, implement, and test your ideas quickly is crucial.\n\nWhat we’re looking for:\n\n-3+ years of industry experience; M.S. in Computer Science or other relevant technical field preferred.\n-3+ years experience collaborating with data science and data engineering teams to build and productionize machine learning pipelines.\n-Fluent in SQL and Python; experience using Spark (pyspark) and working with both relational and non-relational databases.\n-Demonstrated industry success in building and deploying machine learning pipelines, as well as feature engineering from semi-structured data.\n-Solid understanding of the foundational concepts of machine learning and artificial intelligence.\n-A desire to grow as an engineer through collaboration with a diverse team, code reviews, and learning new languages/technologies.\n-2+ years of experience using version control, especially Git.\n-Familiarity with Linux, AWS, Redshift.\n-Deep learning experience preferred.\n-Work experience with REST APIs, deploying microservices, and Docker is a plus.\n\nAbout Doximity\n\nWe’re thrilled to be named the Fastest Growing Company in the Bay Area, and one of Fast Company’s Most Innovative Companies. Joining Doximity means being part of an incredibly talented and humble team. We work on amazing products that over 70% of US doctors (and over one million healthcare professionals) use to make their busy lives a little easier. We’re driven by the goal of improving inefficiencies in our $2.5 trillion U.S. healthcare system and love creating technology that has a real, meaningful impact on people’s lives. To learn more about our team, culture, and users, check out our careers page, company blog, and engineering blog. We’re growing fast, and there’s plenty of opportunity for you to make an impact—join us!\n\nDoximity is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. \n\nPlease mention the words **BARELY INVOLVE INNER** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4yMjQ=). 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 Git, Python, Machine Learning, Engineer, Linux and Medical jobs that are similar:\n\n $75,000 — $122,500/year\n

Doximity is transforming the healthcare industry. Our mission is to help doctors save time so they can provide better care for patients.\n\nWe value diversity — in backgrounds and in experiences. Healthcare is a universal concern, and we need people from all backgrounds to help build the future of healthcare. Our data science team is deliberate and self-reflective about the kind of data team and culture that we are building, seeking data scientists and engineers that are not only strong in their own aptitudes but care deeply about supporting each other's growth. We have one of the richest healthcare datasets in the world, and our team brings a diverse set of technical and cultural backgrounds.\n\nDoximity’s social network has over 70% of US doctors as members and 40M connections among them. We currently are looking for a data scientist to lead a team of other data scientists, data engineers and data analysts with the goal of utilizing this medical graph to better connect and promote discussion among our clinician members.\n\nHow you’ll make an impact:\n\n-Build link prediction models to recommend colleagues for our members to connect and engage with (the “people you may know” problem) to increase user engagement across Doximity’s platforms.\n-Leverage data from Doximity’s social graph to improve the user personalization models that recommend medical and social content to our clinician members.\n-Discover trends and new business opportunities from physician’s medical claims and referral networks.\n-Provide technical leadership to other data scientists and data engineers working on our growth and colleaguing product teams.\n\nWhat we’re looking for:\n\n-4+ years of industry experience and M.S./Ph.D. in Computer Science, Engineering, Statistics, or other relevant technical field.\n-4+ years experience with various machine learning methods (classification, clustering, natural language processing, ensemble methods) and parameters that affect their performance.\n-Experience applying graph theory, analytics, and processing to industry problems.\n-Solid engineering skills to build scalable solutions and help automate data processing challenges.\n-Desire to provide technical leadership and mentorship to other data team members.\n-Excellent problem-solving skills and ability to connect data science work to product impacts.\n-Fluent in SQL and Python; experience using Apache Spark (pyspark)\n-Experience working with relational and non-relational databases.\n\nNice to have:\n\n-Experience with neo4j and either Spark GraphX or GraphFrames for performing graph analytics\n\nAbout Doximity\n\nWe’re thrilled to be named the Fastest Growing Company in the Bay Area, and one of Fast Company’s Most Innovative Companies. Joining Doximity means being part of an incredibly talented and humble team. We work on amazing products that over 70% of US doctors (and over one million healthcare professionals) use to make their busy lives a little easier. We’re driven by the goal of improving inefficiencies in our $2.5 trillion U.S. healthcare system and love creating technology that has a real, meaningful impact on people’s lives. To learn more about our team, culture, and users, check out our careers page, company blog, and engineering blog. We’re growing fast, and there’s plenty of opportunity for you to make an impact—join us!\n\nDoximity is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. \n\nPlease mention the words **SKIN PROUD MAJOR** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4yMjQ=). 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, Stats, Medical and Apache jobs that are similar:\n\n $80,000 — $125,000/year\n

Doximity is the leading online medical network with over 70% of U.S. doctors as members. We have strong revenues, profits, real market traction, and we’re putting a dent in the inefficiencies of our $2.5 trillion U.S. healthcare system. After the iPhone, Doximity is the fastest adopted product by doctors of all time. Launched by Jeff Tangney in 2011; Jeff previously founded healthcare pioneer Epocrates (NASDAQ: EPOC). Our beautiful offices are located in SoMa San Francisco.\n##Skills & Requirements\n- 4+ years of industry experience and M.S./Ph.D. in Computer Science, Engineering, Statistics, or other relevant technical field.\n- 4+ years experience with various machine learning methods (classification, clustering, natural language processing, ensemble methods, deep learning) and parameters that affect their performance.\n- Expert knowledge of probability and statistics (e.g., experimental design, optimization, predictive modeling).\n- Experience with recommendation algorithms and strong knowledge of machine learning concepts.\nSolid engineering skills to build scalable solutions and help automate data processing challenges.\n- Excellent problem-solving skills and ability to connect data science work to product impacts.\n- Fluent in SQL and Python; experience using Apache Spark (pyspark) and working with both relational and non-relational databases.\n- Familiarity with AWS, Redshift.\n\n##What you can expect\n- Employ scalable statistical methods and NLP methods to develop machine learning models at scale, owning them from inception to business impact.\n- Leverage knowledge of recommendation algorithms to increase user engagement through personalization of delivered content.\n- Plan, engineer and measure outcomes of online experiments to help guide product development.\n- Collaborate with a team of product managers, analysts, data engineers, data scientists, and other developers.\n- Think creatively and outside of the box. The ability to implement and test your ideas quickly is crucial.\n\n##Technical Stack\n- We historically favor Python and MySQL, but leverage other tools when appropriate for the job at hand.\n- Machine learning (linear/logistic regression, ensemble-models, boosted-models, clustering, NLP, text categorization, user modeling, collaborative filtering, etc) via industry-standard packages (sklearn, nltk, -Spark ML/MLlib, GraphX/GraphFrames, NetworkX, gensim).\n- A dedicated cluster is maintained to run Apache Spark for computationally intensive tasks.\n- Storage solutions: Percona, Redshift, S3, HDFS, Hive, neo4j.\n- Computational resources: EC2, Spark.\n- Workflow management: Airflow.\n\n##Fun facts about the Data Science team\n- We have access to one of the richest healthcare datasets in the world, with deep information on hundreds of thousands of healthcare professionals and their connections.\n- We build code that addresses user needs, solves business problems, and streamlines internal processes.\n- The members of our team bring a diverse set of technical and cultural backgrounds.\n- Business decisions at Doximity are driven by our data, analyses, and insights.\n- Hundreds of thousands of healthcare professionals will utilize the products you build.\n- A couple times a year we run a co-op where you can pick a few people you'd like to work with and drive a specific company goal.\n- We like to have fun - company outings, team lunches, and happy hours! \n\nPlease mention the words **LIFE DISAGREE TREND** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4yMjQ=). 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, Apache, Medical and Engineer jobs that are similar:\n\n $80,000 — $125,000/year\n

Why work at Doximity?\n\nDoximity is the leading social network for healthcare professionals with over 70% of U.S. doctors as members. We have strong revenues, real market traction, and we're putting a dent in the inefficiencies of our $2.5 trillion U.S. healthcare system. After the iPhone, Doximity is the fastest adopted product by doctors of all time. Our founder, Jeff Tangney, is the founder & former President and COO of Epocrates (IPO in 2010), and Nate Gross is the founder of digital health accelerator RockHealth. Our investors include top venture capital firms who've invested in Box, Salesforce, Skype, SpaceX, Tesla Motors, Twitter, Tumblr, Mulesoft, and Yammer. Our beautiful offices are located in SoMa San Francisco.\n\nSkills & Requirements\n\n-3+ years of industry experience; M.S. in Computer Science or other relevant technical field preferred.\n-3+ years experience collaborating with data science and data engineering teams to build and productionize machine learning pipelines.\n-Fluent in SQL and Python; experience using Spark (pyspark) and working with both relational and non-relational databases.\n-Demonstrated industry success in building and deploying machine learning pipelines, as well as feature engineering from semi-structured data.\n-Solid understanding of the foundational concepts of machine learning and artificial intelligence.\n-A desire to grow as an engineer through collaboration with a diverse team, code reviews, and learning new languages/technologies.\n-2+ years of experience using version control, especially Git.\n-Familiarity with Linux, AWS, Redshift.\n-Deep learning experience preferred.\n-Work experience with REST APIs, deploying microservices, and Docker is a plus.\n\nWhat you can expect\n\n-Employ appropriate methods to develop performant machine learning models at scale, owning them from inception to business impact.\n-Plan, engineer, and deploy both batch-processed and real-time data science solutions to increase user engagement with Doximity’s products.\n-Collaborate cross-functionally with data engineers and software engineers to architect and implement infrastructure in support of Doximity’s data science platform.\n-Improve the accuracy, runtime, scalability and reliability of machine intelligence systems\n-Think creatively and outside of the box. The ability to formulate, implement, and test your ideas quickly is crucial.\n\nTechnical Stack\n\n-We historically favor Python and MySQL (SQLAlchemy), but leverage other tools when appropriate for the job at hand.\n-Machine learning (linear/logistic regression, ensemble models, boosted models, deep learning models, clustering, NLP, text categorization, user modeling, collaborative filtering, topic modeling, etc) via industry-standard packages (sklearn, Keras, NLTK, Spark ML/MLlib, GraphX/GraphFrames, NetworkX, gensim).\n-A dedicated cluster is maintained to run Apache Spark for computationally intensive tasks.\n-Storage solutions: Percona, Redshift, S3, HDFS, Hive, Neo4j, and Elasticsearch.\n-Computational resources: EC2, Spark.\n-Workflow management: Airflow.\n\nFun facts about the Data Science team\n\n-We have one of the richest healthcare datasets in the world.\n-We build code that addresses user needs, solves business problems, and streamlines internal processes.\n-The members of our team bring a diverse set of technical and cultural backgrounds.\n-Business decisions at Doximity are driven by our data, analyses, and insights.\n-Hundreds of thousands of healthcare professionals will utilize the products you build.\n-A couple times a year we run a co-op where you can pick a few people you'd like to work with and drive a specific company goal.\n-We like to have fun - company outings, team lunches, and happy hours! \n\nPlease mention the words **WAVE SPOT WORTH** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4yMjQ=). 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 Git, Python, Machine Learning, Data Science, Engineer, Linux, Docker and Apache jobs that are similar:\n\n $80,000 — $122,500/year\n