Senior ML Platform Engineer - Production-Grade Pipelines

Datavant; Atlanta (GA); On-site; USD 224,000 - 280,000; Full time

Job summary

Datavant seeks a Staff ML Platform Engineer to lead the ML Platform team, guiding the paved road from notebook to production, managing training, serving, and observability. You will own architectural decisions and drive self-serve workflows for Data Science teams, leveraging Databricks, SageMaker, and MLflow while ensuring PHI-safe handling and cost awareness.

You will mentor engineers, write high-leverage code and IaC, and collaborate across Data Science, App Dev, and Operations to deliver a

Qualifications

• 10+ years of software engineering experience; 3+ years building enterprise ML platforms.
• Hands-on with Databricks, SageMaker, and MLflow for tracking and registry.
• Fluency in Java and Python; strong Spark for large-scale data.
• Experience serving LLMs in production and cost management.

Responsibilities

• Set technical direction across ML training, serving, and observability
• Own and evolve paved-road framework for Data Science teams to production workflows
• Lead architecture for LLM-endpoint serving across providers and self-hosted deployments
• Own standards and tooling for MLflow, model registry, training image supply chain
• Partner with Data & ML Platform teammates to present cohesive ML platform
• Contribute to vendor and platform selection decisions for ML tooling
• Mentor senior engineers and contribute code and IaC alongside teammates

Skills

Software engineering

ML platform design

Databricks

SageMaker

Java

Python

Apache Spark

Terraform

Kubernetes

CI/CD for ML

LLM serving

Cost management

Communication

Tools

MLflow

Databricks Asset Bundles

Unity Catalog

Iceberg

Delta Lake

Job description

Datavant seeks a Staff ML Platform Engineer to lead the ML Platform team, guiding the paved road from notebook to production, managing training, serving, and observability. You will own architectural decisions and drive self-serve workflows for Data Science teams, leveraging Databricks, SageMaker, and MLflow while ensuring PHI-safe handling and cost awareness.

You will mentor engineers, write high-leverage code and IaC, and collaborate across Data Science, App Dev, and Operations to deliver a