Artificial Intelligence & Machine Learning Engineer
$77,600–$176,000 year
On-siteArlington, Virginia, United States
Job Summary
Design, train, test, deploy, and maintain end-to-end AI/ML systems, ensuring models perform reliably in production. Own and define the direction of mission-critical solutions by selecting best-fit algorithms, architecting pipelines, and applying modern MLOps practices. Collaborate with data engineers, data scientists, software engineers, and product owners to deliver solutions for the Defense sector, guiding clients through AI/ML strategies and tools. This role requires 4+ years of experience with production-grade AI/ML models, LLMs, and frameworks like TensorFlow or PyTorch, along with a Secret clearance and a Bachelor's degree. Compensation ranges from $77,600 to $176,000 annually. Booz Allen delivers advanced technology solutions for America's critical defense and national security priorities.
Required Qualifications
- 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
- Ability to train, optimize, and integrate AI/ML algorithms across high throughput text, image, or video data feeds
- Secret clearance
- Bachelor's degree
- Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information
- TS/SCI clearance
Desired Qualifications
- 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
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