Architect ML Platform for Production-Grade AI

Datavant; Sacramento (CA); Remote; USD 224,000 - 280,000; Full time

Job summary

Datavant is seeking a Staff ML Platform Engineer to lead our Data & ML Platform group. You will drive the paved road for ML training, serving, and observability, and own architecture for LLM-endpoint serving across multiple providers.

You will mentor engineers, influence platform standards, and contribute hands-on code and IaC in a remote, async-friendly environment. The role requires deep experience with Databricks, SageMaker, MLflow, Spark, and cloud services, plus strong Java/Python skills

Qualifications

• 10+ years of software engineering experience, with 3+ years designing, evolving, and operating enterprise-scale ML platforms in production.
• Strong technical judgment under ambiguity and a track record of setting standards, influencing peers, and raising the bar across teams.
• Hands-on production experience with Databricks and/or Amazon SageMaker, MLflow (or equivalent), and at least one core ML framework (PyTorch, TensorFlow, or similar).
• Fluency in Java (or a JVM equivalent) and Python, with depth in Apache Spark 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-based CI/CD for ML workflows.
• Direct experience serving LLMs in production, including cost management and safe handling of prompts.
• AI-native working style with daily use of Claude Code, Cursor, Copilot, etc.
• Clear written and verbal communication in async, remote settings.

Responsibilities

• Set technical direction across ML training, serving, and observability; be the escalation point for advanced infra problems.
• Own and evolve our paved-road framework so DS teams can go from config to production without bespoke plumbing.
• Lead architecture for LLM-endpoint serving across managed and self-hosted deployments, focusing on latency and cost.
• Own standards and tooling for MLflow, model registry, training image supply chain, and observability.
• Partner with Data & ML Platform teammates to present a cohesive ML platform to Data Science, App Dev, and Operations teams.
• Serve as key input to vendor and platform selection decisions across model providers and tooling.
• Mentor senior engineers, provide guidance to platform consumers, and contribute hands-on IaC work.

Skills

Software engineering

ML platform design

Production experience

Java

Python

Apache Spark

AWS

Terraform

Kubernetes

LLM serving

Tools

Databricks

Amazon SageMaker

MLflow

Terraform

Kubernetes

GitHub Actions / CI/CD

Iceberg/Delta tables

Job description

Datavant is seeking a Staff ML Platform Engineer to lead our Data & ML Platform group. You will drive the paved road for ML training, serving, and observability, and own architecture for LLM-endpoint serving across multiple providers.

You will mentor engineers, influence platform standards, and contribute hands-on code and IaC in a remote, async-friendly environment. The role requires deep experience with Databricks, SageMaker, MLflow, Spark, and cloud services, plus strong Java/Python skills