Booz Allen Hamilton

AI/ML Engineer, Mid

Dayton, OH, US$77,500-$176,000Posted 18 days ago

Job Description

The Opportunity

As an Artificial Intelligence and Machine Learning (AI/ML) Engineer, you will help design, build, and implement practical AI/ML capabilities that enhance mission systems and 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 sof tware engineering practices, consistent with the company’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.

What You'll Work On

  • Develop and implement AI-engineered signal-processing and automation tools and capabilities for EO / IR 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.

Join us. The world can’t wait.

You Have

  • 4+ years of experience developing AI / ML capabilities to operate in a microservice stack
  • Experience devising AI-agent planning, reasoning, and execution loops
  • Experience with Python-based ML frameworks such as PyTorch or TensorFlow
  • Experience demonstrating statically-sound model evaluation and AI quality met rics
  • Experience building, deploying, and operating production ML models using either supervised, unsupervised, or anomaly de...

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