Senior MLOps Engineer
Core
Design and operate production ML/LLM platforms for healthcare workflows, focusing on model development, deployment, monitoring, and compliance.
Role type
Senior MLOps Engineer (Healthcare)
Builds
End-to-end ML/LLM delivery pipelines, CI/CD systems, feature stores, and observability dashboards for regulated environments.
Domain
Healthcare + Machine Learning Operations
Deliverable
production ML models
Required skills
Python, ML engineering, LLM orchestration, GCP services, containerization, Kubernetes, CI/CD, model monitoring, data governance
Preferred skills
Vertex AI, managed vector search, RAG, guardrails implementation, distributed training
Technologies
Python, GCP, GKE, Cloud Run, Docker, Kubernetes, Vertex AI, Cloud Run
Responsibilities
Design and operate ML platforms supporting data ingestion, training, evaluation, and deployment; Build and maintain CI/CD pipelines for ML/LLM systems; Implement model monitoring and observability for performance and drift; Develop scalable training infrastructure with GPU scheduling; Create feature pipelines and stores to prevent training-serving skew; Build LLM evaluation harnesses with human-in-the-loop workflows; Integrate security guardrails and content filters for LLM outputs.
Seniority
Senior, hands-on IC
