Tempus

Staff/Senior Machine Learning Engineer, Clinical AI

Chicago, IL, US$150,000-$230,000Posted 1 month ago

Job Description

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.

We're seeking a highly skilled and innovative Staff/Senior Machine Learning Engineer to join our Clinical AI Team. As a Staff/Senior Machine Learning Engineer, you'll play a crucial role in leveraging and deploying cutting-edge natural language processing models and LLMs specifically tailored for healthcare applications at scale. Your work will contribute to optimizing clinical workflows, improving clinical trial matching, and advancing medical research. This position offers an exciting opportunity to leverage the power of natural language processing and LLMs to revolutionize healthcare and make a significant impact on people's lives.

What You Will Do

  • Build and operate production AI pipelines: LLM-powered extraction, batch orchestration, and inference, with a focus on reliability, cost, and latency
  • Design and maintain Airflow-based orchestration for batch clinical workflows
  • Build the observability (metrics, logging, alerting) that catches regressions before they reach downstream consumers
  • Build and maintain eval infrastructure that measures clinical model output quality continuously: regression detection, drift, gold-set management, dashboards
  • Ship platform tooling and SDKs that accelerate Machine Learning Scientists and downstream consumers
  • Partner with Machine Learning Scientists to debug bad model outputs to root cause (data, prompt, or pipeline)
  • Participate in the pod's on-call rotation
  • Collaborate with platform / infrastructure teams to leverage GCP services for performance, security, an...

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