Health at Scale is the market leader in precision health -- digital health
programs that offer smart, hyper-personalized insights to help individuals
choose the best providers, treatments, care settings and lifestyle choices for
their unique healthcare needs. Founded by leading machine learning and
clinical faculty from MIT, Stanford, Harvard and the University of Michigan,
we work with some of the largest payers, employers and providers in the U.S.
to improve outcomes, costs, access, and equity for their members. Health at
Scale operates some of the largest deployments of AI in healthcare to date,
covering millions of lives in production settings. We have been recognized for
our innovation and as one of the fastest growing private companies by Forbes,
Fast Company, Inc 500, UCSF Digital Health, Becker's, TechCrunch, Bloomberg
and MIT News. For more information, please visit our website.
As a senior machine learning engineer at Health at Scale, you will work with
an exceptional team of engineers, scientists, and clinicians to design,
engineer, test, deploy and maintain machine intelligence platforms and
applications for real-world production use. You will iterate and improve upon
the machine intelligence technologies in each of our products. You will be the
point person for translating machine learning innovations into impactful
products with new customers and transforming leading-edge ideas into
production-ready, real-time solutions that will serve millions of users.
Responsibilities
* Design, engineer, test, deploy and maintain machine intelligence platforms and applications for real-world production use at scale
* Improve the accuracy, runtime, scalability and reliability of machine intelligence algorithms and software
* Develop and implement machine intelligence platform APIs for multiple use-cases
* Drive architecture of platform and application capabilities embedding machine intelligence
* Develop prototyped solutions and translate leading-edge ideas into production-ready systems
* Ensure seamless interactions between data pipelines and machine learning pipelines in development and production environments
Requirements
* BS, MS or PhD in Computer Science or related technical field
* 2+ years of full-time industry employment building and scaling end-to-end ML pipelines for production and working with large, real-world datasets
* Strong understanding of the foundational concepts of machine learning and artificial intelligence
* Strong proficiency in Python (preferred), Java, or C/C++
* Proven experience in evaluating, debugging, and improving ML models
* Proficiency in writing unit tests and using automated testing tools
* Excellent communication skills
Health at Scale is an equal opportunity employer and is committed to diversity
in its hiring and business practices. To all recruitment agencies: Health at
Scale does not accept agency resumes. Please do not forward resumes to this
job alias, company employees or any organization location. Health at Scale is
not responsible for any fees related to unsolicited resumes.
