Senior ML Platform Engineer - Scale Production AI

Datavant; Trenton (NJ); On-site; USD 224,000 - 280,000; Full time

Job summary

Datavant is seeking a Staff ML Platform Engineer to lead the ML Platform team responsible for moving models from notebook to production. You will set direction, own architectural challenges, and empower Data Science teams to self-serve across Databricks, AWS, and self-hosted deployments with focus on latency, cost, and PHI-safe routing.

This role requires AI fluency, hands-on coding, and strong collaboration with platform teammates in a remote-friendly environment.

Qualifications

• 10+ years of software engineering experience, with 3+ years designing, evolving, and operating enterprise-scale ML platforms in production.
• Experience with Databricks and SageMaker, MLflow, and PyTorch/TensorFlow or similar.
• Strong technical judgment and ability to set standards across teams.

Responsibilities

• Set technical direction across ML training, serving, and observability, and be the final escalation point for the most elusive infrastructure problems.
• Own and evolve the paved-road framework so Data Science teams can go from a config file to a production workflow.
• Lead architecture for LLM-endpoint serving across managed providers and self-hosted deployments with PHI-safe routing.
• Own the standards and tooling for MLflow, model registry, and training image supply chain.
• Mentor senior engineers and contribute high-leverage code and IaC alongside teammates.

Job description

Datavant is seeking a Staff ML Platform Engineer to lead the ML Platform team responsible for moving models from notebook to production. You will set direction, own architectural challenges, and empower Data Science teams to self-serve across Databricks, AWS, and self-hosted deployments with focus on latency, cost, and PHI-safe routing.

This role requires AI fluency, hands-on coding, and strong collaboration with platform teammates in a remote-friendly environment.