Staff/Senior Machine Learning Engineer, Clinical AI

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, and cost-efficiency

• Author and review design docs for cross-pod work

• Raise the engineering bar through code review and design review

Required Qualifications:

• Strong command of Python in production environments

• Experience designing, building, and integrating with microservices in production

• Deployed data orchestration workflows in production (Airflow or equivalent)

• Worked on cloud-native services (GCP preferred but not required)

• Built monitoring, observability, and alerting for production systems

• Hands-on experience with at least one major ML framework — we primarily use LangGraph; PyTorch, spaCy, or equivalents are equally welcome

• Strong written and verbal communication, including experience authoring and reviewing design docs (RFCs, PRDs, or equivalent); partners well with research scientists, PMs, and clinicians

Preferred Qualifications:

• Operated production systems hands-on — on-call rotations, incident response, postmortems

• Experience building eval / quality measurement systems for ML or LLM outputs

• Hands-on production LLM application experience (prompts, agents, RAG, LLM evals, extraction pipelines)

• Built internal platforms or SDKs that other engineers / scientists depended on

• Experience working with clinical or biomedical data (EHR, genomics, pathology, clinical notes)

• Contributions to relevant open-source projects

#LI-BL1

New York Pay Range - $170,000 - $230,000 USD

California Pay Range - $170,000 - $230,000 USD

Illinois Pay Range - $150,000 - $210,000 USD

Remote - USA Range - $150,000 - $210,000 USD

The expected salary range above is applicable if the role is performed from California and may vary for other locations (Colorado, Illinois, New York). Actual salary may vary based on qualifications and experience. Tempus offers a full range of benefits, which may include incentive compensation, restricted stock units, medical and other benefits depending on the position.

We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.