Staff ML Platform Engineer: Scale Production AI Pipelines

Aimlroles; Northern (KY); Hybrid; USD 224,000 - 280,000; Full time

Job summary

Datavant seeks a Staff ML Platform Engineer to lead the ML platform effort in our Data & ML Platform group. You will own the paved road for training, serving, and observability, while driving architecture for LLM-endpoint serving and self-serve pipelines across Databricks, AWS, and self-hosted environments.

You will mentor engineers, set technical standards, and contribute hands-on IaC and core code. The role emphasizes AI fluency, HIPAA-aware handling, and collaboration with cross-functional

Qualifications

• 10+ years of software engineering experience with 3+ years designing, evolving, and operating enterprise-scale ML platforms in production.
• Hands-on production use of Databricks and/or Amazon SageMaker, MLflow (or equivalent), and at least one core ML framework.
• Fluency in Java and Python, with deep Apache Spark experience for large-scale data and distributed compute.
• Real depth in AWS: networking, IAM, GPU compute, and related services.
• Fluency with Terraform, containers, Kubernetes, and GitHub CI/CD for ML workloads.
• Direct experience serving LLMs in production, including cost management and safe handling of prompts.
• AI-native workflow: daily use of Claude Code, Cursor, Copilot, etc., in engineering work,
• Clear written and verbal communication, especially async, remote settings.

Responsibilities

• Set technical direction across ML training, serving, and observability, and be the escalation point for complex infrastructure issues (GPU capacity, Spark tuning, production incidents).
• Own and evolve our paved-road framework (CI/CD spine, model-workflow scaffolding, Databricks Asset Bundles) for fast production workflows from config files.
• Lead architecture for LLM-endpoint serving across managed providers and self-hosted deployments, covering latency, cost, caching, evaluation, and PHI-safe routing.
• Own standards for MLflow, model registry, training image supply chain, and observability across training and inference.
• Partner with Data & ML Platform teammates to present a cohesive ML platform to Data Science, App Dev, and Operations teams.

Skills

ML Platform design

AWS & cloud

Databricks

SageMaker

MLflow

Python

Java

Spark

Terraform

Kubernetes

Tools

Databricks

SageMaker

MLflow

PyTorch

TensorFlow

Apache Spark

Unity Catalog

Iceberg/Delta

Terraform

GitHub Actions

Job description

Datavant seeks a Staff ML Platform Engineer to lead the ML platform effort in our Data & ML Platform group. You will own the paved road for training, serving, and observability, while driving architecture for LLM-endpoint serving and self-serve pipelines across Databricks, AWS, and self-hosted environments.

You will mentor engineers, set technical standards, and contribute hands-on IaC and core code. The role emphasizes AI fluency, HIPAA-aware handling, and collaboration with cross-functional