Staff/Senior Machine Learning Engineer, Clinical AI

Experteer Overview As a Staff/Senior Machine Learning Engineer on Tempus’s Clinical AI Team, you will build and operate production AI pipelines centered on LLMs and healthcare-specific NLP. You will design scalable systems that improve clinical workflows, trial matching, and medical research, delivering real-time, actionable insights to clinicians. You’ll work closely with researchers and engineers to debug model outputs, monitor quality, and ensure secure, cost-efficient cloud deployments. This role offers the chance to shape AI tooling that accelerates clinical decision-making at scale, impacting patient care. You will join a mission-driven team developing real-world evidence platforms that connect data to 0 Compensation / Benefits * Build and operate production AI pipelines for LLM-powered extraction, batch orchestration, and inference * Design and maintain Airflow-based orchestration for batch clinical workflows * Develop observability through metrics, logging, and alerting to catch regressions * Create and maintain eval infrastructure to measure clinical model output quality, including drift and regression detection * Ship platform tooling and SDKs to accelerate ML Scientists and downstream consumers * Collaborate with ML Scientists to root-cause bad model outputs (data, prompts, or pipelines) * 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 and design reviews Tasks * 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 (LangGraph; PyTorch, spaCy, or equivalents) * Strong written and verbal communication, including authoring and reviewing design docs Key requirements * incentive compensation * restricted stock units * medical benefits

AI regressions * Create and maintain eval infrastructure to measure clinical model output quality, including drift and regression detection * Ship platform tooling and SDKs to accelerate ML Scientists and downstream consumers * Collaborate with ML Scientists to root-cause bad model outputs (data, prompts, or pipelines) * 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 and design reviews Tasks * 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 (LangGraph; PyTorch, spaCy, or equivalents) * Strong written and verbal communication, including authoring and reviewing design docs Key requirements * incentive compensation * restricted stock units * medical benefits