AI/ML Engineer

Booz Allen Hamilton•Fort Meade, MD

1d•$99,000 - $225,000•Remote

About The Position

As an experienced engineer, you know that building reliable and scalable AI systems requires far more than just model development—it demands strong software engineering practices, automation, and seamless integration across complex environments. Your ability to design and maintain robust AI/ML pipelines, automate workflows, and integrate AI capabilities into production systems makes you an essential part of delivering resilient, mission-focused solutions. We need your technical expertise and problem‑solving mindset to support the development and operationalization of AI capabilities that directly enhance mission performance and decision‑making. As an AI and ML engineer on our national security team, you’ll build, test, deploy, and operate software end‑to‑end AI pipelines that keep mission systems running securely and efficiently. In this role, you’ll guide the development of mission‑critical AI solutions by building reproducible pipelines, applying automation best practices, and introducing emerging tools that enhance performance and reliability. You’ll collaborate with a cross‑functional team of AI Model Engineers, Data Engineers, Cloud Architects, and ISSEs to align AI and ML workflows with infrastructure and security requirements, ensuring seamless integration into production and mission systems. You’ll contribute to solutions that optimize data flow, automate operational workflows, ensure monitoring and observability, and support resilient mission execution across hybrid compute environments. Your engineering skills and experience with modern AI and ML frameworks will help clients navigate evolving toolchains, deployment patterns, and operational considerations for scalable AI systems. Work with us to build reliable AI pipelines, modernize mission workflows, and define AI and ML strategy. Join us. The world can’t wait.

Requirements

6+ years of experience with software engineering
Experience with Python
Experience developing and maintaining AI and ML pipelines for model training, validation, and deployment
Experience integrating AI and ML capabilities into production systems and mission workflows
Experience implementing monitoring and observability solutions for model performance, resource utilization, and system health
Knowledge of hybrid compute environments such as cloud and on‑prem
Ability to automate workflows and build reproducible, scalable, and efficient ML and AI systems
Ability to collaborate with cross‑functional teams, such as AI Model Engineers, Data Engineers, Cloud Architects, or ISSE, to align workflows with infrastructure and security requirement
TS/SCI clearance with a polygraph
HS diploma or GED

Nice To Haves

10+ years of experience with software engineering
Experience with Rust for systems‑level or high‑performance components
Experience evaluating or adopting emerging AI and ML frameworks, libraries, or toolchains
Experience with containerization or orchestration technologies such as Docker or Kubernetes
Experience in cloud services relevant to AI and ML such as AWS or Azure
Knowledge of CI/CD for ML pipelines or infrastructure‑as‑code such as Terraform or CloudFormation
Knowledge of ML or MLOps orchestration tools such as, Airflow, Kubeflow, or MLflow
Knowledge of distributed training, GPU optimization, or advanced model deployment patterns
Bachelor’s degree

Responsibilities

Build, test, deploy, and operate software end‑to‑end AI pipelines.
Guide the development of mission‑critical AI solutions by building reproducible pipelines.
Apply automation best practices and introduce emerging tools that enhance performance and reliability.
Collaborate with a cross‑functional team of AI Model Engineers, Data Engineers, Cloud Architects, and ISSEs to align AI and ML workflows with infrastructure and security requirements.
Contribute to solutions that optimize data flow, automate operational workflows, ensure monitoring and observability, and support resilient mission execution across hybrid compute environments.
Help clients navigate evolving toolchains, deployment patterns, and operational considerations for scalable AI systems.