MLOps Engineer

Role Overview

As an MLOps Engineer on Booz Allen Hamilton’s Air Power team, you will help develop and deliver a working Agentic AI Platform. You will train, test, deploy, and maintain machine learning models, guiding solution direction through best-fit ML approaches and emerging technologies.

Responsibilities

• Train, test, deploy, and maintain production-grade ML models
• Apply ML algorithms to drive critical solutions and define ML strategy for Air Force agentic systems
• Manage ML workloads and design elastic, scalable infrastructure for cost-effective resource management
• Lead technical direction by collaborating across AI software engineers, DevSecOps, and Data Engineers
• Share ML knowledge with a broader community of machine learning engineers
• Support Agentic AI platform development in a team environment

Requirements

• Experience deploying production-grade ML models to cloud environments
• Experience managing ML workloads and designing elastic infrastructure for scaling and cost effectiveness
• Knowledge of MLOps frameworks and container systems (e.g., Kubernetes or Docker)
• Bachelor’s degree in Computer Science or Software Engineering

Compensation

• Projected salary range: $128,700 – $292,000 (annualized USD) (dependent on factors such as location and experience)