Staff ML Platform Engineer

Job Summary

To support the Data & ML Platform organization, the full-time Staff ML Platform Engineer will set technical direction for ML training and serving, own architectural solutions for LLM-endpoint serving, and evolve the paved-road framework to enable Data Science teams to deploy models effectively in a remote environment.

Key responsibilities

• Set technical direction across ML training, serving, and observability while addressing complex infrastructure problems
• Own and evolve the paved-road framework to facilitate seamless production workflows for Data Science teams
• Lead architecture for LLM-endpoint serving, ensuring efficient management of latency, cost, and PHI-safe routing

Required qualifications

• 10+ years of software engineering experience, with at least 3 years in enterprise-scale ML platforms
• Hands-on experience with Databricks, Amazon SageMaker, and MLflow or similar systems
• Proficiency in Java (or JVM equivalent) and Python, with expertise in Apache Spark
• Strong knowledge of AWS services relevant to ML workloads, including networking and GPU compute
• Experience with Terraform, containers, Kubernetes, and CI/CD for ML applications