Staff/Senior Machine Learning Engineer, Clinical AI

Experteer Overview In this role you will design, deploy, and operate production AI pipelines that power healthcare-focused NLP and LLM applications. You’ll contribute to clinical workflows, trial matching, and biomedical research by delivering reliable, scalable AI capabilities. You will work with cross-functional teams to improve real-time insights for physicians and patients, shaping how AI supports clinical decision making. This position offers a chance to innovate at scale in a mission-driven clinical AI environment, with a strong emphasis on observability, reliability, and performance. Compensation / Benefits * Build and operate production AI pipelines for LLM-powered extraction, orchestration, and inference * Design and maintain Airflow-based orchestration for batch clinical workflows * Develop observability (metrics, logging, alerting) to detect regressions * Build and maintain evaluation infrastructure for continuous model output quality assessment * Ship platform tooling and SDKs to accelerate ML Scientists and downstream users * Collaborate with ML Scientists to diagnose and root-cause bad model outputs * Participate in on-call rotations * Collaborate with platform/infrastructure teams to leverage GCP services for performance, security, and cost efficiency * Author and review design docs for cross-pod work * Contribute to code and design reviews to raise engineering standards Tasks * Strong command of Python in production * Experience designing, building, and integrating with microservices in production * Deployed data orchestration workflows (Airflow or equivalent) * Cloud-native services experience (GCP preferred) * Monitoring, observability, and alerting for production systems * Hands-on experience with major ML frameworks (LangGraph; PyTorch, spaCy, or equivalents) Key requirements * incentive compensation * restricted stock units * medical benefits * remote-friendly options * position-dependent benefits

_ SDKs to accelerate ML Scientists and downstream users * Collaborate with ML Scientists to diagnose and root-cause bad model outputs * Participate in on-call rotations * Collaborate with platform/infrastructure teams to leverage GCP services for performance, security, and cost efficiency * Author and review design docs for cross-pod work * Contribute to code and design reviews to raise engineering standards Tasks * Strong command of Python in production * Experience designing, building, and integrating with microservices in production * Deployed data orchestration workflows (Airflow or equivalent) * Cloud-native services experience (GCP preferred) * Monitoring, observability, and alerting for production systems * Hands-on experience with major ML frameworks (LangGraph; PyTorch, spaCy, or equivalents) Key requirements * incentive compensation * restricted stock units * medical benefits * remote-friendly options * position-dependent benefits