Machine Learning Software Engineer, Cardio

Redwood City, California, United States, Chicago, Illinois, United States, New York, New York, United States

Tempus logo
Tempus
Apply now Apply later

Posted 3 weeks ago

Passionate about precision medicine and advancing the healthcare industry?

Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.

Passionate about building great software products?

At Tempus, software products are owned and developed by small, autonomous teams composed of developers, designers, scientists, and product managers. Your team helps to set goals, build the software, deploy the code, and contribute to a growing software platform that will make a lasting impact in the field of cancer research and treatment. Tempus Insights is our business to develop, validate and launch new predictive tests, in oncology and new disease areas, by leveraging our clinical + molecular + imaging data to provide novel insights to clinicians and patients.

Tempus builds software as nimble as our teams. Our modern full-stack tech stack - React and Node.js on AWS - allows our teams to iterate rapidly and lead our industry in innovation. Our decentralized, microservice architecture and emphasis on automation allow us to deliver  advanced solutions with confidence, and at scale 

This person makes core contributions to the FDA device builds for Cardio. Their core responsibility is to understand, test, and ship the models including production infra for retraining.

Outcomes: This Engineer will build the inputs and outputs for deploying cardio models; integrate with other Tempus systems as needed (i.e. OrderHub, Data Products) but primarily focus on an end to end solution for Afib.

Competencies:

  • Large system architecture - has successfully launched products that encompass multiple systems and teams and integrated with external systems or APIs
  • Machine learning models and techniques - has deployed models in prod, and has some experience with deep neural networks. They won't be developing new models but need to be able to debug and make changes and refactors.
  • Detail-oriented communication - will need to write and understand the FDA regulations and keep track of all changes for auditability
  • Bonus: experience with any of the following would be attractive but is not required:
    • FDA-regulated medical devices
    • Electronic medical systems integrations
    • Large data ingestion and processing
Job tags: AI AWS Healthcare Machine Learning Research