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Remote Health by SafetyWing
Global health insurance for freelancers & remote workers
Machine Learning Engineerverified closed
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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 engineering team is deliberate and self-reflective about the kind of team and culture that we are building, seeking engineers that are not only strong in their own aptitudes but care deeply about supporting each other's growth.\n\nOur team brings a diverse set of technical and cultural backgrounds and we like to think pragmatically in choosing the tools most appropriate for the job at hand. We deploy our applications to production on average 50 times per day and have over 350 private repositories in Github, ranging from forks of gems, our own internal gems as well as auxiliary applications. Check out more on the Doximity engineering blog. \n\n**How you’ll make an impact:**\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\n**What we’re looking for:**\n* 5+ 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* 3+ years of experience using version control, especially Git.\n* Familiarity with Linux and AWS.\n* Deep learning experience preferred.\n* Work experience with REST APIs, deploying microservices, and Docker is a plus.\n\n**About 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\n*Doximity 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.*
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