Posted over 1 year agoOverview Doximity is transforming the healthcare industry. Our mission is to help doctors save time so they can provide better care for patients. We 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. How you’ll make an impact: Employ appropriate methods to develop performant machine learning models at scale, owning them from inception to business impact. Plan, engineer, and deploy both batch-processed and real-time data science solutions to increase user engagement with Doximity’s products. Collaborate cross-functionally with data engineers and software engineers to architect and implement infrastructure in support of Doximity’s data science platform. Improve the accuracy, runtime, scalability and reliability of machine intelligence systems Think creatively and outside of the box. The ability to formulate, implement, and test your ideas quickly is crucial. What we’re looking for: 3+ years of industry experience; M.S. in Computer Science or other relevant technical field preferred. 3+ years experience collaborating with data science and data engineering teams to build and productionize machine learning pipelines. Fluent in SQL and Python; experience using Spark (pyspark) and working with both relational and non-relational databases. Demonstrated industry success in building and deploying machine learning pipelines, as well as feature engineering from semi-structured data. Solid understanding of the foundational concepts of machine learning and artificial intelligence. A desire to grow as an engineer through collaboration with a diverse team, code reviews, and learning new languages/technologies. 2+ years of experience using version control, especially Git. Familiarity with Linux, AWS, Redshift. Deep learning experience preferred. Work experience with REST APIs, deploying microservices, and Docker is a plus.