Machine Learning Engineer

Doximity · Remote, USA · April 23, 2018


Undisclosed Salary

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.

Python Sql Spark Machine Learning Aws Linux Docker Git