AI/ML Engineer, Mid

Booz Allen Hamilton•Aurora, CO

9d•Remote

About The Position

As an AI/ML Engineer at Booz Allen, you will help design, build, and implement practical artificial intelligence and machine learning capabilities that enhance OPIR missions to support faster, more informed decision‑making across the national security ecosystem. You will contribute across the development lifecycle—supporting data processing, model creation, MLOps workflows, and the integration of scalable AI solutions into operational environments—while working closely with senior engineers and mission partners. Your work will leverage deep experience with ML‑based NLP, LLMs and generative AI, computer vision, and modern software engineering practices, consistent with the firm’s AI/ML engineering role definitions. You will partner closely with cross‑functional engineering, mission SMEs, and product teams to deliver production‑grade systems aligned with Booz Allen’s AI modernization approaches.

Requirements

4+ years of experience developing AI/ML capabilities to operate in a microservice stack
Experience with devising AI-agent planning, reasoning, and execution loops
Experience with Python-based ML frameworks such as PyTorch or TensorFlow
Experience with demonstrating statically-sound model evaluation and AI quality metrics
Experience building, deploying, and operating production ML models using either supervised, unsupervised, or anomaly detection efforts
Active TS/SCI clearance; willingness to take a polygraph exam
Bachelor's degree in a STEM field

Nice To Haves

Experience in GPU programming, including CUDA or RAPIDs
Experience with AWS and containerization of models in a classified environment
Experience with ML engineering and MLOps, including model versioning, CI/CD for ML, monitoring, drift detection, and automated retraining
Knowledge of modern software design patterns, including micro-service design and orchestration in Kubernetes deployment
Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field

Responsibilities

Develop and implement AI-engineered signal-processing and automation tools and capabilities for domain applications
Collaborate with multidisciplinary teams to design, develop, test, and deploy technical solutions in support of modernizing analysis workflows
Utilize GPU programming, including CUDA or RAPIDs, to optimize the performance of applications and processes
Contribute to the architecture and implementation of novel approaches for rapidly fielding capabilities, including using streaming data sets and NRT feeds