Staff ML Platform Engineer
Core
Building the production ML platform (training, inference, serving) for healthcare AI products, enabling Data Science teams to move models from notebook to production safely.
Role type
Staff ML Platform Engineer (Technical Lead)
Builds
Enterprise-scale ML pipelines, LLM endpoints, and observability infrastructure for regulated health data.
Domain
Healthcare technology / Machine Learning Infrastructure
Deliverable
production ML models | infrastructure
Required skills
Enterprise ML platform design, Databricks, Amazon SageMaker, MLflow, Java, Python, Apache Spark, AWS (networking, IAM, GPU), Terraform, Kubernetes, CI/CD, LLM serving, AI-native tooling (Claude Code, Cursor, Copilot)
Preferred skills
Healthcare/regulated industry experience (HIPAA, HITRUST), Databricks Asset Bundles, specialized inference pipelines, GPU capacity planning, streaming platforms (Kafka, Kinesis), open-source ML contributions
Responsibilities
Set technical direction for ML training and serving, own the paved-road framework for model deployment, lead LLM endpoint architecture, manage MLflow and observability standards, mentor senior engineers, write high-leverage code and IaC
Seniority
Staff, technical leadership & hands-on IC
