\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

[NEURONBITS](http://neuronbits.com) is going through an extensive growth fase. We are looking for people who are sharp, creative and hardworking, with an unwavering desire to be the best. In return we provide a competetive compensation package, a friendly, challenging, and motivating working environment.\n\n**All positions at Neuronbits are fully remote**\n\nRenumeration package\n\n- € 40 - 60k / year\n- 25 days paid holidays\n\n\n**Job description**\n\nAs Machine Learning Engineer at Neuronbits you will support us to improve the quality of our data and possibilities to analyze our data to get a competitive advantage.\n\n\n**Primary responsibilities:**\n\n- Applies supervised and unsupervised learning techniques for solving pattern recognition problems (detection, classification, regression).\n\n- Maintain and improve machine learning models in production and build new ones.\n\n- Understands and interprets data to come up with optimal feature sets.\n\n- Prepares datasets to train and validate models.\n\n- Deploys the machine learning algorithms into production environment.\n\n- Documents and presents the work in a complete and consistent way.\n\n\n**Ideally, you’ll have:**\n\n- At least 3 years of experience in Machine Learning / Data Science.\n\n- Good knowledge and proven experience in supervised/unsupervised learning in different applications: image recognition, classification, recommendation, etc.\n\n- Proven experience in deploying and maintaining Machine Learning algorithms in production.\n\n- Solid programming skills in Python, ++ and/or Java\n\n- Experience in Apache Spark with Scala\n\n- Background on Hadoop ecosystem (Hive, Sqoop, Oozie....).\n\n- Knowledge on databases (SQL and NoSQL). \n\nPlease mention the words **BIRTH CURTAIN HARVEST** when applying to show you read the job post completely (#RMjE2LjczLjIxNi4yMzU=). 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, Engineer and Apache jobs that are similar:\n\n $80,000 — $120,000/year\n \n\n#Location\nWorldwide

About you:\n\n\n* Care deeply about democratizing access to data.  \n\n* Passionate about big data and are excited by seemingly-impossible challenges.\n\n* At least 80% of people who have worked with you put you in the top 10% of the people they have worked with.\n\n* You think life is too short to work with B-players.\n\n* You are entrepreneurial and want to work in a super fact-paced environment where the solutions aren’t already predefined.\n\n\n\nAbout SafeGraph: \n\n\n\n* SafeGraph is a B2B data company that sells to data scientists and machine learning engineers. \n\n* SafeGraph's goal is to be the place for all information about physical Places\n\n* SafeGraph currently has 20+ people and has raised a $20 million Series A.  CEO previously was founder and CEO of LiveRamp (NYSE:RAMP).\n\n* Company is growing fast, over $10M ARR, and is currently profitable. \n\n* Company is based in San Francisco but about 50% of the team is remote (all in the U.S.). We get the entire company together in the same place every month.\n\n\n\n\nAbout the role:\n\n\n* Core software engineer.\n\n* Reporting to SafeGraph's CTO.\n\n* Work as an individual contributor.  \n\n* Opportunities for future leadership.\n\n\n\n\nRequirements:\n\n\n* You have at least 6 years of relevant work experience.\n\n* Deep understanding of machine learning models, data analysis, and both supervised and unsupervised learning methods. \n\n* Proficiency writing production-quality code, preferably in Scala, Java, or Python.\n\n* Experience working with huge data sets. \n\n* You are authorized to work in the U.S.\n\n* Excellent communication skills.\n\n* You are amazingly entrepreneurial.\n\n* You want to help build a massive company. \n\n\n\nNice to haves:\n\n\n* Experience using Apache Spark to solve production-scale problems.\n\n* Experience with AWS.\n\n* Experience with building ML models from the ground up.\n\n* Experience working with huge data sets.\n\n* Python, Database and Systems Design, Scala, TensorFlow, Apache Spark, Hadoop MapReduce.\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, Senior and Apache 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

\nJavaScript Engineer\n\nAt Elastic, we have a simple goal: to pursue the world's data problems with products that delight and inspire. We help people around the world do exceptional things with their data. From stock quotes to Twitter streams, Apache logs to WordPress blogs, our products are extending what's possible with data, delivering on the promise that good things come from connecting the dots. Often, what you can do with our products is only limited by what you can dream up. We believe that diversity drives our vibe. We unite Elasticians across 30+ countries into one unified team, while the broader community spans across over 100 countries\n\nMachine Learning at Elastic\n\nMachine Learning (ML) for the Elastic Stack allows users to better understand the behavior of their data. We have developed an unsupervised machine learning engine that can plow through large amounts of data and automatically find those insights our users today have been proactively finding using search. Current use cases include finding anomalies within transactions / operational metrics, detecting uncharacteristic user behavior or finding malicious devices.\n\nWe have an exciting roadmap and are looking to hire an extraordinary Software Engineer to join us. You will have an amazing opportunity to join a small, highly experienced team where you can make an immediate impact and contribution to the development of our new machine learning offerings.\n\nWhat you will be doing\n\nAs a member of the team, you will contribute to the further development and ongoing maintenance of our ML focussed projects.\n\nThe ML user interface has to be both beautifully designed to help users to get insight out of their data and also operationally usable allowing them to easily set-up, configure and operationally manage their ML analysis jobs.\n\nYou do not need to be a machine learning expert, however you do need to be comfortable working in a data driven development environment using large complex datasets.\n\nIn addition, you will be working closely with data, integration, analytics and QA engineers, as well as collaborating with the core Kibana team and the amazing Elastic Stack community.\n\nWhat you will bring\n\n\n* Strong front-end JavaScript, HTML, CSS experience (+2yrs)\n\n* Experienced with JavaScript-based front-end web application frameworks\n\n* Deep understanding of UX/UI design principles\n\n* Ready to be part of a dedicated distributed team, having strong collaboration and communication skills\n\n* Strong analytical, problem solving, debugging and troubleshooting skills\n\n* Experience writing automated tests\n\n\n\n\nExperience in these areas is a plus\n\n\n* Knowledge, interest and a real passion for topics in data visualisations, statistics, machine learning, data analytics\n\n* Educational background in a mathematical discipline such as Mathematics, Physics, Engineering, Computer Science\n\n* Knowledge of IT Operations, IT Infrastructure, Application Performance Monitoring and/or IT Security domains\n\n\n\n\nAdditional Information\n\nWe're looking to hire team members invested in realizing the goal of making real-time data exploration easy and available to anyone. As a distributed company, we believe that diversity drives our vibe! Whether you're looking to launch a new career or grow an existing one, Elastic is the type of company where you can balance great work with great life.\n\n#LI-AD1\n\nElastic is an Equal Employment employer committed to the principles of equal employment opportunity and affirmative action for all applicants and employees. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status or any other basis protected by federal, state or local law, ordinance or regulation. Elastic also makes reasonable accommodations for disabled employees consistent with applicable law. \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Machine Learning, CSS, Engineer 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

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

\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

\nAt Elastic, we have a simple goal: to pursue the world's data problems with products that delight and inspire. We help people around the world do exceptional things with their data. From stock quotes to Twitter streams, Apache logs to WordPress blogs, our products are extending what's possible with data, delivering on the promise that good things come from connecting the dots. Often, what you can do with our products is only limited by what you can dream up. We believe that diversity drives our vibe. We unite Elasticians across 30+ countries into one unified team, while the broader community spans across over 100 countries\n\nMachine Learning at Elastic\n\nMachine Learning (ML) for the Elastic Stack allows users to better understand the behavior of their data. We have developed an unsupervised machine learning engine that can plow through large amounts of data and automatically find those insights our users today have been proactively finding using search. Current use cases include finding anomalies within transactions / operational metrics, detecting uncharacteristic user behavior or finding malicious devices.\n\nWe have an exciting roadmap and are looking to hire an extraordinary Software Engineer to join us. You will have an amazing opportunity to join a small, highly experienced team where you can make an immediate impact and contribution to the development of our new machine learning offerings.\n\nWhat you will be doing\n\nAs a member of the team, you will contribute to the further development and ongoing maintenance of our ML focussed projects and the integration of our core ML algorithms and code into the Elastic Stack. You do not need to be a machine learning expert, however you do need to be comfortable working in a data driven development environment using large complex datasets to ensure analytical and operational performance. Day to day, the majority of your development tasks will be in Java, but familiarity and experience with C++ and JavaScript is useful. In addition, you will be working closely with data, UI and QA engineers, as well as collaborating with the core Elasticsearch team and the Elastic Stack community.\n\nWhat you will bring\n\n\n* Educational background in a mathematical discipline such as Mathematics, Physics, Engineering, Computer Science\n\n* Strong Java Experience (+2yrs industry experience)\n\n* Deep understanding of JVM internals including garbage collection, the memory model, etc.\n\n* C++ experience (although this may not have been in your most recent role)\n\n* Ready to be part of a dedicated distributed team, having strong collaboration and communication skills\n\n* Experience in developing complex (secure, high speed, low latency, high-throughput, multi-threaded) systems\n\n\n\n\nExperience in these areas is a plus\n\n\n* Knowledge of IT Operations, IT Infrastructure, Application Performance Monitoring and/or IT Security domains\n\n* Knowledge, interest and a real passion for topics in statistics, machine learning, data analytics and/or data visualization\n\n\n\n\nAdditional Information\n\nWe're looking to hire team members invested in realizing the goal of making real-time data exploration easy and available to anyone. As a distributed company, we believe that diversity drives our vibe! Whether you're looking to launch a new career or grow an existing one, Elastic is the type of company where you can balance great work with great life.\n\n\n* Competitive pay based on the work you do here and not your previous salary\n\n* Equity\n\n* Global minimum of 16 weeks of paid in full parental leave (moms & dads)\n\n* Generous vacation time and one week of volunteer time off\n\n* Your age is only a number. It doesn't matter if you're just out of college or your children are; we need you for what you can do.\n\n\n\n\n#LI-MD1\n\nElastic is an Equal Employment employer committed to the principles of equal employment opportunity and affirmative action for all applicants and employees. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status or any other basis protected by federal, state or local law, ordinance or regulation. Elastic also makes reasonable accommodations for disabled employees consistent with applicable law. \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Machine Learning, JavaScript, Elasticsearch, Java, Engineer and Apache jobs that are similar:\n\n $70,000 — $120,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n

\nInformation Engineer\n\nAt Elastic, we have a simple goal: to solve the world's data problems with products that delight and inspire. As the company behind the popular open source projects — Elasticsearch, Kibana, Logstash, and Beats — we help people around the world do great things with their data. From stock quotes to real time Twitter streams, Apache logs to WordPress blogs, our products are extending what's possible with data, delivering on the promise that good things come from connecting the dots. The Elastic family unites employees across 30+ countries into one coherent team, while the broader community spans across over 100 countries.\n\nMachine Learning at Elastic \n\nMachine Learning (ML) for the Elastic Stack allows users to better understand the behavior of their data. We have developed an unsupervised machine learning engine that can plow through large amounts of data and automatically find those insights our users today have been proactively finding using search. Current use cases include finding anomalies within transactions / operational metrics, detecting uncharacteristic user behavior or finding malicious devices.\n\nTo help us further expand our capabilities we are looking fo an exceptional individual who can support us in our insatiable appetite for data. This is an amazing opportunity to join a small, highly experienced team where you can make an immediate impact and contribution to the development of our new machine learning offerings.\n\nWhat you will be doing\n\nTo support data driven development of engineering features by becoming a super-user of our ML tool set, by making meaningful data accessible to engineers and in helping to maintain and improve the quality of results. Responsibilities will include:\n\n\n* Curate and extend data library - develop, acquire and catalog datasets representative of core customer use cases\n\n* Perform data analysis on complex datasets and clearly describe and communicate findings to peers\n\n* Develop ML job configs for known uses cases\n\n* Develop standardized labeling techniques for datasets in our catalog. For example, known outliers or anomalies (unsupervised), or output labels (supervised).\n\n* Build statistical robustness tests for machine learning models against an ever growing data catalog\n\n* Follow GDPR policies, security and data license requirements where applicable\n\n\n\n\nYour background\n\n\n* Highly numerate with education background in Mathematics, Computer Science, Information/Library science, Physics, Engineering or similar\n\n* Solid industry experience working with data; for example as a data analyst, software-, QA engineer or similar\n\n\n\n\nWhat you will bring\n\n\n* A proven ability to work with large amounts of data (at least 2 years)\n\n* Able to work as part of a distributed team, having strong collaboration and communication skills\n\n* Detail oriented with a librarian-like approach to organization\n\n* Able to analyse real-world datasets and extract insights according to customer use case\n\n* Knowledge, interest and a real passion for topics in big data, machine learning, data mining and statistical analysis\n\n\n\n\nExperience required in some or all of these areas\n\n\n* Software engineering (Python, Java, C++)\n\n* Statistical packages and tools (e.g. R, SAS, Octave, MATLAB etc)\n\n* Visualization technologies\n\n* NoSQL or relational databases\n\n\n\n\nAdditional Information: \n\nWe're looking to hire team members invested in realizing the goal of making real-time data exploration easy and available to anyone. As a distributed company, we believe that diversity drives our vibe! Whether you're looking to launch a new career or grow an existing one, Elastic is the type of company where you can balance great work with great life.\n\n\n* Competitive pay based on the work you do here and not your previous salary\n\n* Stock options\n\n* Global minimum of 16 weeks of paid in full parental leave (moms & dads)\n\n* Generous vacation time and one week of volunteer time off\n\n* Your age is only a number. It doesn't matter if you're just out of college or your children are; we need you for what you can do.\n\n\n\n\n#LI-MD1\n\nElastic is an Equal Employment employer committed to the principles of equal employment opportunity and affirmative action for all applicants and employees. Applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status or any other basis protected by federal, state or local law, ordinance or regulation. Elastic also makes reasonable accommodations for disabled employees consistent with applicable law. \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, Education and Apache 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

\nSenior Machine Learning Engineer\n\nSummary:\n\nSenior Machine Learning Engineer to join Selerity’s team, scaling up an A.I. driven analytics and recommendation platform and integrating it into enterprise workflows.  Highly competitive compensation plus significant opportunities for professional growth and career advancement.\n\nEmployment Type: Contract or Full-time\n\nLocation is flexible: We have offices in New York City and Oak Park, Illinois (Chicago suburb) but about half of our team currently works remotely from various parts of Europe, North America, and Asia.  \n\n\nJob Description:\n\nWant to change how the world engages with chat, research, social media, news, and data?\n\nSelerity has dominated ultra-low-latency data science in finance for almost a decade.  Now our real-time content analytics and contextual recommendation platform is gaining broader traction in enterprise and media applications.  We're tackling big challenges in predictive analytics, conversational interfaces, and workflow automation and need your help!\n\nWe’re looking for an experienced Machine Learning Engineer to join a major initiative at a critical point in our company’s growth.  This is a hands-on role, applying the latest technology in natural language processing and machine learning (including deep learning) to real-world problems in capital markets, institutional research, financial news, and social media.  Machines are playing an ever-increasing role in finance and we're leading that trend.\n\n\nMust-haves:\n\n* Possess a rock-solid background in Computer Science (minimum BS in Comp Sci or related field) + at least 5 years (ideally 10+) of challenging work experience.\n\n* Rigorous understanding of data science foundations and theory including algorithms, statistics, experimental setup, etc.\n\n* Experience applying NLP and/or machine learning to large-scale datasets, especially text.\n\n* Experience with large-scale analytics and machine learning technologies including TensorFlow/Sonnet, Torch, Caffe, Spark, Hadoop, cuDNN, etc.\n\n* Advanced proficiency working in Java in Linux environments.\n\n* Significant operational experience with deploying, monitoring, and maintaining large-scale A.I. applications in production environments.  Not just research and prototypes.\n\n* Solid track record of making effective design decisions balancing near-term and long-term objectives.\n\n* Know when to use commercial or open-source solutions, when to delegate to a teammate, and when to roll up your sleeves and code it yourself.\n\n* Work effectively in agile teams with remote members; get stuff done with minimal guidance and zero BS, help others, and know when to ask for help.\n\n* Clearly communicate complex technical and product issues to non-technical team members, managers, clients, etc.  \n\n\nNice-to-haves:\n\n* Advanced degree (MS/PhD) in a quantitative field such as Computer Science or Statistics.\n\n* Proficiency in C++, Python, Scala, or other commonly-used languages.\n\n* Experience with analytics visualization libraries.\n\n* Conversant with relational, column, object, and graph database fundamentals and strong practical experience in any of those paradigms.\n\n* Deep understanding of how to build software agents and conversational workflows.\n\n* Knowledge of capital markets concepts, entities, and processes.\n\n\nOur stack:\n\n* Java, C++, Python, JavaScript/ECMAscript + Node, Angular, Electron, Scala, etc.\n\n* A variety of open source and in-house frameworks for natural language processing and machine learning including artificial neural networks / deep learning.\n\n* Hybrid of AWS (EC2, S3, RDS, R53) + dedicated datacenter network, server and GPU/coprocessor infrastructure.\n\n* Cassandra, Aurora plus in-house streaming analytics pipeline (similar to Apache Flink) and indexing/query engine (similar to ElasticSearch).\n\n* In-house messaging frameworks for low-latency (sub-microsecond sensitivity) multicast and global-scale TCP (similarities to protobufs/FixFast/zeromq/itch).\n\n* Ansible, Git, Subversion, PagerDuty, Icinga, Grafana, Observium, LDAP, Jenkins, Maven, Purify, VisualVM, Wireshark, Eclipse, IntelliJ.\n\nThis position offers a great opportunity to work with advanced technologies, collaborate with a top-notch, global team, and disrupt a highly visible, multi-billion-dollar market.  \n\n\n\nCompensation:\n\nWe understand how to attract and retain the best talent and offer a competitive mix of salary, benefits and equity.  We also understand how important it is for you to feel challenged, to have opportunities to learn new things, to have the flexibility to balance your work and personal life, and to know that your work has impact in the real world.\n\nWe have team members on four continents and we're adept at making remote workers feel like part of the team.  If you join our NYC main office be sure to bring your Nerf toys, your drones and your maker gear - we’re into that stuff, too.\n\n\n\nInterview Process:\n\nIf you can see yourself at Selerity, send your resume and/or online profile (e.g. LinkedIn) to [email protected].  We’ll arrange a short introductory phone call and if it sounds like there’s a match we'll arrange for you to meet the team for a full interview.  \n\nThe interview process lasts several hours and is sometimes split across two days on site, or about two weeks with remote interviews.  It is intended to be challenging - but the developers you meet and the topics you’ll be asked to explain (and code!) should give you a clear sense of what it would be like to work at Selerity.  \n\nWe value different perspectives and have built a team that reflects that diversity while maintaining the highest standards of excellence.  You can rest assured that we welcome talented engineers regardless of their age, gender, sexual orientation, religion, ethnicity or national origin.\n\n\n\n\n\nRecruiters: Please note that we are not currently accepting referrals from recruiters for this 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, Engineer, Finance, Java, Apache and Linux jobs that are similar:\n\n $70,000 — $120,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n

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 (#RMjE2LjczLjIxNi4yMzU=). 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. 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 (#RMjE2LjczLjIxNi4yMzU=). 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

\nAt Elastic, we have a simple goal: to pursue the world's data problems with products that delight and inspire. We help people around the world do exceptional things with their data. From stock quotes to Twitter streams, Apache logs to WordPress blogs, our products are extending what's possible with data, delivering on the promise that good things come from connecting the dots. Often, what you can do with our products is only limited by what you can dream up. We believe that diversity drives our vibe. We unite Elasticians across 30+ countries into one unified team, while the broader community spans across over 100 countries\n\nMachine Learning at Elastic\n\nMachine Learning (ML) for the Elastic Stack allows users to better understand the behavior of their data. We have developed an unsupervised machine learning engine that can plow through large amounts of data and automatically find those insights our users today have been proactively finding using search. Current use cases include finding anomalies within transactions / operational metrics, detecting uncharacteristic user behavior or finding malicious devices.\n\nTo help us further expand our capabilities we are looking to hire an extraordinary individual who can support us in our insatiable appetite for data. You will have an amazing opportunity to join a small, dedicated and highly experienced team where you can make an immediate impact and contribution to the development of our new machine learning offerings.\n\nWhat you will be doing\n\nYou will support the data driven development of engineering features by making the data accessible to engineers and data scientists.\n\n\n* Curate and extend data libraries - develop, acquire and catalog datasets representative of core customer use cases\n\n* Extract, transform and load relevant data to accessible data formats\n\n* Develop, support and maintain data collection infrastructures using our Elastic Stack\n\n* Perform data analysis on complex datasets and clearly describe and communicate findings to peers\n\n* Follow GDPR policies, security and data license requirements where applicable\n\n\n\n\nWhat you will bring\n\n\n* A BS, MS or PhD in an applied data science discipline such as Mathematics, Physics, Engineering or similar\n\n* Practical industry experience (at least a few years) working in a data engineering or data analysis role\n\n* Proven ability to work with large data sets\n\n* Ready to be part of a dedicated distributed team, having strong collaboration and communication skills\n\n* Able to plan, prioritize and deliver complex data projects\n\n* Knowledge, interest and a real passion for topics in big data, machine learning, mining of data and statistical analysis\n\n* Able to analyse real-world datasets and extract insights according to a customer use case\n\n\n\n\nYou are experienced in one or more of the following\n\n\n* Statistical packages and tools (e.g. R, SAS, Octave, MATLAB, etc)\n\n* Scripting languages (e.g. Unix Shell scripts, Python, etc)\n\n* Visualization technologies (Matplotlib, Seaborn, d3, etc)\n\n* NoSQL or relational databases\n\n* Working with big amounts of data on AWS/Cloud platforms is a huge plus\n\n\n\n\nAdditional Information\n\n\n* Competitive pay and benefits\n\n* Stock options\n\n* Catered lunches, snacks, and beverages in most offices\n\n* An environment in which you can balance great work with a great life\n\n* Passionate people building great products\n\n* Employees with a wide variety of interests\n\n* Distributed-first company with employees in over 30 countries, spread across 18 time zones, and speaking over 30 languages!\n\n\n\n\nElastic is an Equal Employment employer committed to the principles of equal employment opportunity and affirmative action for all applicants and employees. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status or any other basis protected by federal, state or local law, ordinance or regulation. Elastic also makes reasonable accommodations for disabled employees consistent with applicable law. \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 Apache 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

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 (#RMjE2LjczLjIxNi4yMzU=). 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 (#RMjE2LjczLjIxNi4yMzU=). 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