Lead ML Platform Engineer: Scale Production Pipelines

Datavant; Tallahassee (FL); Remote; USD 224,000 - 280,000; Full time

Job summary

Datavant is seeking a Staff ML Platform Engineer to join our Data & ML Platform organization. We own the paved road that takes a model from notebook to production, covering training, inference on SageMaker and Databricks, self‑service LLM endpoints, and the pipelines behind our clinical‑AI products.

You will lead architecture, set direction for the platform, and mentor senior engineers while remaining hands‑on with IaC and core code. AI fluency and secure handling of PHI data are required.

Qualifications

• 10+ years of software engineering, with 3+ years designing enterprise-scale ML platforms.
• Strong technical judgment and ability to set standards across teams.
• Hands-on production experience with Databricks and/or SageMaker, MLflow, and a core ML framework.
• Fluency in Java and Python; Deep Spark experience for large-scale data.
• AWS experience including networking, IAM, GPU compute; knowledge of storage and messaging services.
• Terraform, containers, Kubernetes, and GitHub CI/CD for ML workloads.
• Experience serving LLMs in production with cost management and safe handling of prompts.
• AI-native workflow with Claude Code, Cursor, Copilot, etc.
• Clear written and verbal communication in async, remote settings.

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 our paved-road framework (the shared CI/CD spine, model-workflow scaffolding, and Databricks Asset Bundles) so Data Science teams can go from a config file to a production workflow without bespoke plumbing.
• Lead architecture for LLM-endpoint serving across managed providers (Databricks, AWS, Snowflake) and self-hosted deployments, covering latency, cost, caching, evaluation, and PHI-safe routing.
• Own the standards and tooling for MLflow, model registry, training image supply chain, and observability across training and inference.
• Partner closely with your Data & ML Platform teammates to present a cohesive ML platform to the Data Science, App Dev, and Operations teams at Datavant.
• Serve as a key technical input to vendor and platform selection decisions across model providers, ML tooling, and observability.
• Mentor senior engineers on the team, provide technical guidance to platform consumers, and stay hands-on writing high-leverage code and Infrastructure-as-Code alongside your teammates.

Skills

Software engineering

Java

Python

Apache Spark

AWS

Databricks

SageMaker

Terraform

Kubernetes

ML CI/CD

Tools

Databricks

SageMaker

MLflow

Terraform

Kubernetes

GitHub Actions

Iceberg/Delta

Job description

Datavant is seeking a Staff ML Platform Engineer to join our Data & ML Platform organization. We own the paved road that takes a model from notebook to production, covering training, inference on SageMaker and Databricks, self‑service LLM endpoints, and the pipelines behind our clinical‑AI products.

You will lead architecture, set direction for the platform, and mentor senior engineers while remaining hands‑on with IaC and core code. AI fluency and secure handling of PHI data are required.