Staff/Senior Machine Learning Engineer, Clinical AI

Experteer Overview In this role you apply NLP and LLMs at scale to improve clinical workflows, trial matching, and research. You’ll build production AI pipelines, monitor performance, and collaborate with researchers and clinicians to deliver real-time, actionable insights. You will help shape a healthcare AI platform that accelerates decision making and outcomes. This is a chance to impact patient care through robust, observable AI systems and cross-functional collaboration. Compensation / Benefits * Build and operate production AI pipelines including LLM-powered extraction, batch orchestration, and inference * Design and maintain Airflow-based orchestration for batch clinical workflows * Develop observability (metrics, logging, alerting) to detect regressions * Create eval infrastructure to measure clinical model output quality (drift, gold-set management, dashboards) * Ship platform tooling and SDKs to accelerate ML Scientists and downstream users * Collaborate with ML Scientists to debug model outputs to root cause (data, prompts, or pipelines) * Participate in 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 engineering bar through code and design reviews Tasks * Strong command of Python in production * 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) * 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 design docs (RFCs, PRDs) Key requirements * incentive compensation * restricted stock units * medical benefits * other position-related benefits * remote-friendly policies * diverse, inclusive environment

to debug model outputs to root cause (data, prompts, or pipelines) * Participate in 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 engineering bar through code and design reviews Tasks * Strong command of Python in production * 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) * 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 design docs (RFCs, PRDs) Key requirements * incentive compensation * restricted stock units * medical benefits * other position-related benefits * remote-friendly policies * diverse, inclusive environment