Tempus

Staff/Senior Machine Learning Engineer, Clinical AI

Tempus$170K — $230K *
Healthcare
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Proficient in Python for production use.
  • Experience building microservices in operational settings.
  • Familiar with deploying data workflows, preferably with Airflow.
  • Hands-on with cloud-native services, especially GCP.
  • Skilled in monitoring and observability of systems.
  • Experience with major ML frameworks, notably LangGraph, PyTorch, or spaCy.
  • Strong communication skills for drafting and reviewing technical documents.

Responsibilities

  • Build and maintain AI pipelines for reliability and efficiency.
  • Design clinical workflow orchestration using Airflow.
  • Develop observability metrics to prevent production regressions.
  • Continuously measure the quality of clinical model outputs.
  • Create tools and SDKs to assist Machine Learning Scientists.
  • Collaborate to identify root causes of model output issues.
  • Engage in on-call support as part of team duties.
  • Work with infrastructure teams to optimize GCP services.

Benefits

  • Comprehensive health insurance options.
  • Incentive compensation plans.
  • Access to restricted stock units.
  • Support for professional development opportunities.
Full Job Description

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.

About Tempus

Tempus is a technology company that has built an operating system to battle cancer. The company enables physicians to deliver personalized cancer care for patients through its interactive analytical and machine learning platform. Tempus provides genomic sequencing services and analyzes molecular and therapeutic data to empower physicians to make real-time, data-driven decisions. The company also offers research services to enable discovery of new therapeutic targets and clinical services that support clinical trial design and monitoring. Tempus was founded in 2015 by Eric Lefkofsky and has raised over $8 billion in funding to date.
Learn more about Tempus
Size
1,001 employees
Industry
Founded
2015

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