Artificial Intelligence & Machine Learning Engineer

Booz Allen Hamilton•Arlington, VA

2d•$77,600 - $176,000

About The Position

As an experienced AI/ML engineer, you know that modern machine learning requires more than accurate models, it demands strong engineering practices, thoughtful system design, and the ability to build solutions that perform reliably in production. Your ability to conduct statistical analyses, implement AI/ML techniques, and build robust AI/ML pipelines makes you integral to delivering customer‑focused solutions. We need your technical expertise and problem-solving mindset to support AI/ML missions across the federal government. As an AI/ML engineer on our team, you’ll design, train, test, deploy, and maintain end‑to‑end AI/ML systems, ensuring models perform reliably not just in development, but in production. In this role, you’ll own and define the direction of mission-critical solutions by selecting best‑fit algorithms, architecting AI/ML pipelines, and applying modern MLOps practices. You’ll be part of a talented team of machine learning engineers across the company and collaborate with data engineers, data scientists, software engineers, and product owners to deliver world class solutions. Your skills and technical leadership will guide clients as they navigate the landscape of AI/ML tools, frameworks, and operational strategies. Work with us to solve real-world challenges and define AI/ML strategy for the Defense sector and beyond. Join us. The world can’t wait.

Requirements

4+ years of experience as an Artificial Intelligence/Machine Learning Engineer or Advanced Data Scientist
Experience deploying and integrating production-grade AI/ML models using tools such as Docker or Kubernetes
Experience with Large Language Models (LLMs), Deep Learning (DL) or Reinforcement Learning (RL) algorithms, along with frameworks such as TensorFlow, PyTorch, vLLM, and Ollama
Knowledge of MLOps principles and the design and implementation of machine learning algorithms integrated in operational systems and deployed to production environments
Secret clearance
Bachelor's degree

Nice To Haves

Experience working in cloud environments, such as AWS or Azure
Experience developing production‑quality ML-enabled software components, such as RESTful APIs, microservices, or real‑time inference pipelines
Experience with emerging agentic AI frameworks and understanding of how to integrate agent‑based systems into production environments
TS/SCI clearance
Master's degree

Responsibilities

Design, train, test, deploy, and maintain end‑to‑end AI/ML systems.
Select best‑fit algorithms, architect AI/ML pipelines, and apply modern MLOps practices.
Conduct statistical analyses.
Implement AI/ML techniques.
Build robust AI/ML pipelines.
Train, optimize, and integrate AI/ML algorithms across high throughput text, image, or video data feeds.