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EEOC

AI/ML Software Engineer

EEOC

AI/ML Software Engineer at Booz Allen focusing on cloud deployment and innovation for health outcomes. Collaborating with scientists and engineers for advanced R&D projects.

Posted 6/2/2026full-timeWashington • District of Columbia, Texas, Washington • 🇺🇸 United StatesMid-LevelSenior💰 $69,400 - $158,000 per yearWebsite

Tech Stack

Tools & technologies
AWSAzureCloudETLPythonPyTorchTensorflow

About the role

Key responsibilities & impact
  • Deploy AI models and services on cloud platforms such as AWS, Google Cloud, or Azure
  • Collaborate with cross-functional teams, including data scientists, researchers, and other engineers, to integrate LLMs and RAG into broader projects
  • Extend agentic capabilities, including agent orchestration and tools calling, using MCP and A2A
  • Communicate technical concepts and project progress to non-technical stakeholders and team members
  • Conduct experiments to fine-tune parameters and optimize model performance
  • Implement techniques to improve the efficiency and scalability of LLM and RAG systems
  • Stay up-to-date on the most current developments in the generative-AI space
  • Monitor and maintain deployed models to ensure they perform reliably and meet performance benchmarks
  • Ensure code quality by following best practices in software development, including version control, testing, and continuous integration or continuous deployment (CI / CD)

Requirements

What you’ll need
  • 5+ years of experience delivering production-ready, industrial strength code
  • Experience in Python and with libraries such as TensorFlow and PyTorch
  • Experience with neural network architecture, including transformers, and NLP techniques
  • Experience with LLM tool or function calling and agentic orchestration
  • Experience handling and preprocessing large datasets, and with data pipelining and ETL processes
  • Experience with cloud platforms such as AWS, Google Cloud, or Azure, for deploying ML models
  • Experience with software engineering fundamentals, including version control, testing, and CI / CD
  • Ability to design efficient algorithms for data retrieval and model training, and optimize models through hyperparameter tuning
  • Ability to travel up to 25% of the time

Benefits

Comp & perks
  • Health, life, disability, financial, and retirement benefits
  • Paid leave
  • Professional development
  • Tuition assistance
  • Work-life programs
  • Dependent care
  • Recognition awards program

ATS Keywords

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Hard Skills & Tools
PythonTensorFlowPyTorchneural network architecturetransformersNLP techniqueshyperparameter tuningdata pipeliningETL processesalgorithm design
Soft Skills
collaborationcommunicationproject management