We’re a company that makes open source tools for data science and machine learning. You might know us from popular tools like [DVC](https://dvc.org) (Data Version Control) and [CML](https://cml.dev) (Continuous Machine Learning), or our [YouTube channel](https://www.youtube.com/channel/UC37rp97Go-xIX3aNFVHhXfQ). Our team is small, remote-first, and passionate about creating best practices for managing the complexities of data science.\n\nWe’re seeking a Developer Advocate to help us sustain and grow our active, worldwide community! \n\n## Job description\nAs an open source project, our community is everything. Our code, docs and outreach activities are fueled by community contributions, and user feedback is a huge driver for our product development. We invest heavily in building relationships with data scientists, engineers and developers around the world, from brand new contributors making their first pull request to longtime users working out a special use case. \n\nThe ideal candidate will:\n- Craft blog posts, release notes, and newsletters to share exciting developments on our projects, amazing contributions, and important technical Q&As. \n- Turn frequently-asked questions in the community into reusable resources, like tutorials and use-cases\n- Be a connector and maintain an engaged presence online. Respond to timely discussions and questions on social media and design shareable, creative campaigns for regular tweets and posts. \n- Enable community members of all skill levels to get involved. Welcome newcomers and encourage creative contributions. When folks make videos, blogs, or projects with our tools, help them boost the signal.\n- Lead community-building events like virtual meetups and present at relevant industry conferences\n- Be analytical and data-driven in creating useful content for the community. Define, report and analyze metrics to understand our community’s needs and interests.\n\n## Skills we’re looking for\n- Experience in either data science or open source software.\n- Experience blogging or publishing technical content online. Bonus points if it’s related to open source or data science. \n- Experience building and/or managing a technical community.\n- Understanding of Git, Git-flow and CI/CD. You don’t have to be a superuser, but we make tools built around Git and you’ll need to know how to use them.\n- Strong communication skills. Everyone on our team, from engineers to developer advocates, needs to be able to communicate over digital - platforms kindly and clearly.\n- Proficient written and spoken English is required. \n \n### Mega bonus skills\n- Knowledge of our tools and the MLOps space\n- A strong existing network in data science or open source\n\n### Perks\n- A fully remote job with a competitive salary and benefits package.\n- Our team culture is family-friendly. Our leadership includes several working parents, and our health insurance and unlimited PTO policies are designed with families in mind.\n- This role can grow with you. There are plenty of opportunities for leadership and autonomy in our small team! \n- Impact- you get to work on projects that are used every day by teams around the world! DVC and CML are used by researchers and data science teams across tech, finance, and government organizations. \n- You will get a [DeeVee](https://twitter.com/DVCorg/status/1314668966082572288/photo/1). \n\nPlease mention the words **BUILD CRUISE ARMOR** when applying to show you read the job post completely (#RMjE2LjczLjIxNi42MQ==). 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\nWorldwide

**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 (#RMjE2LjczLjIxNi42MQ==). 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)

We’re a company that makes open source tools for data science and machine learning. You might know us from popular tools like [DVC](https://dvc.org) (Data Version Control) and [CML](https://cml.dev) (Continuous Machine Learning), or our [YouTube channel](https://www.youtube.com/channel/UC37rp97Go-xIX3aNFVHhXfQ?). Our team is small, remote-first, and passionate about creating best practices for managing the complexities of data science.\n\nWe’re seeking a **Technical Community Manager** to help us sustain and grow our active, worldwide community! \n\n## Job description\nAs an open source project, our community is everything. Our code, docs and outreach activities are fueled by community contributions, and user feedback is a huge driver for our product development. We invest heavily in building relationships with data scientists, engineers and developers around the world, from brand new contributors making their first pull request to longtime users working out a special use case. \n\nThe ideal candidate will:\n\n* Enable community members of all skill levels to get involved. Welcome newcomers and encourage creative contributions. When folks make videos, blogs, or projects with our tools, help them boost the signal.\n* Be a connector and maintain an engaged presence online. Respond to timely discussions and questions on social media and design shareable, creative campaigns for regular tweets and posts. \n* Make blog posts, release notes, and newsletters to share exciting developments on our projects, amazing contributions, and important technical Q&As. \n* Turn frequently-asked questions in the community into reusable resources, like tutorials and use-cases\n* Lead community-building events like virtual meetups and our ambassador program. \n* Be analytical and data-driven in building and nurturing the community. Define, report and analyze metrics to understand our community’s needs and growth. \n\n\n## Skills we’re looking for\n* Experience in either **data science or open source software**.\n* Experience building and/or managing a ** technical community**.\n* Understanding of Git, Git-flow and CI/CD. You don’t have to be a superuser, but we make tools built around Git and you’ll need to know how to use them.\n* Experience blogging or publishing technical content online. Bonus points if it’s related to open source or data science. \n* Strong communication skills. Everyone on our team, from engineers to developer advocates, needs to be able to communicate over digital platforms kindly and clearly.\n* Proficient written and spoken English is required. \n \n**Mega bonus skills**\n* Knowledge of our tools and the MLOps space\n* A strong existing network in data science or open source\n\n## Perks\n* A fully remote job with a competitive salary and benefits package.\n* Our team culture is family-friendly. Our leadership includes several working parents, and our health insurance and unlimited PTO policies are designed with families in mind.\n* This role can grow with you. There are plenty of opportunities for leadership and autonomy in our small team! \n* Impact- you get to work on projects that are used every day by teams around the world! DVC and CML are used by researchers and data science teams across tech, finance, and government organizations. \n* You will get a DeeVee.\n\n \n\nPlease mention the words **GRASS EXCESS UNVEIL** when applying to show you read the job post completely (#RMjE2LjczLjIxNi42MQ==). 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\nWorldwide

\nPosition: Sr. or Team Lead Machine Learning Engineer, Full Time\n\nLocation: Fully Remote anywhere in the USA or optional office location in SF\n\nAt Cisco Meraki, we know that technology can connect, empower, and drive us. Our mission is to simplify technology so our customers can focus on what's most meaningful to them: their students, patients, customers, and businesses. We’re making networking easier, faster, and smarter with technology that simply works.\n\nAs a Machine Learning engineer on the Insight team, you will collaborate with firmware and full stack engineers to design, plan, and build customer-facing analytics tools. Meraki's cloud-managed model offers a unique opportunity to draw upon data from millions of networks across our wide ranging customer base. The goal is to use the rich telemetry data available from these networks and combine it with the power of machine learning and the cloud to build an analytics engine that can provide intuitive, yet detailed insights into the performance of customer networks.\n\nWhat you can expect:\n\n\n* Build a system that ingests real-time streams of network performance data and identifies network performance degradation, optimizing for both low latency and few false positives\n\n* Design models that predict network performance for customers to help them understand their network performance issues\n\n* Work with firmware and backend engineers to design uplink selection algorithm for SD-WAN\n\n* Collaborate with full stack engineers to make intuitive data visualizations and integrate predictions seamlessly and powerfully into the user experience\n\n* Build, maintain, and monitor data pipelines and infrastructure for training and deploying models\n\n\n\n\nWhat we're ideally looking for:\n\n\n* 5+ years of relevant industry experience\n\n* Advanced training in mathematics, statistics, and modeling\n\n* Experience programming in Python AND some other programming language like scala, golang, ruby, etc.\n\n* Experience working with algorithms and building models for supervised and unsupervised learning.\n\n* Experience using data processing and ML libraries such as Pandas, Scikit-Learn, Tensorflow, Keras, etc.\n\n* Experience working with distributed computing engines like Apache Spark, etc. and real time data streaming services like Amazon Kinesis.\n\n* Experience implementing and monitoring data pipelines.\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, Amazon, Cloud, Python, Apache and Backend 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

\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

\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

\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

Full Time: Machine Learning/AI Lead at Bothouse in Remotely \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Machine Learning and Executive jobs that are similar:\n\n $75,000 — $135,000/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

‼️ [Machine Learning/AI Lead needed!] ‼️\n--------------------------------------------------------------\n\n🕦 Full-time\n\n🌎 Remotely or in our office in Warsaw (Europe), regular flights to Oslo (costs are covered)\n\n💰 $50 - $90 an hour\n\n⌛ Duration: 4 - 12 months with the ability to extend\n\n🏁 Start: beginning of August 2018\n\n🇳🇴 2 week-long visit in Oslo at the beginning of the project\n\n👥 4 people with this profile are needed\n\nYet another time we search for extraordinary people to join our nerdy crew! :)\n\nProject for a big retail corporation in Norway (11k employees) with stores across entire Europe. \nYou’ll be working closely with business people (20 years of business experience), IT specialists (SE architects, DevOps, UI/UX people) and also with board members to design and execute digital transformation to replace client’s entire IT infrastructure with an AI-first, data-oriented, modern, future-proof solution. \n\nThe project involves an above-average degree of machine learning system design, conceptual thinking, algorithmic thinking and communication/brainstorming with business-oriented people/industry specialists. \n\nIf you are looking for an easy next project/job, or quick cash - there are better offers out there.\n\nA rare opportunity to hone not only the technical expertise or English skills, but also business-oriented communication, industry-related, practical business know-how and system design skills. \nWe have people with Google DeepMind on their CVs already involved. \n\nLess experienced folks are also welcome to apply - we need many people.\n\n 👉 Contact: [email protected] \n\nPlease mention the words **MIND EXERCISE RACCOON** when applying to show you read the job post completely (#RMjE2LjczLjIxNi42MQ==). 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, Data Science, Executive and English jobs that are similar:\n\n $75,000 — $122,500/year\n