Reinforcement Learning AI Engineer

Job Number: R0245112

The Opportunity:

Are you an innovative and experienced artificial intelligence developer specializing in reinforcement learning? Utilize your expertise in AI, data science, and machine learning (ML) engineering to train, test, deploy, and maintain models that learn from data to drive real-world mission critical impact. You will collaborate with dynamic teams to translate reinforcement learning research into operational capability and production-grade code, bringing significant technological advancements that drive mission success.

You'll join a growing community of ML engineers focused on delivering products and solutions to our customers' most challenging problems. You'll collaborate with a team of dedicated space, military, intelligence, engineering, and AI professionals to deliver cutting-edge solutions to solve issues of national importance.

• Design, implement, and train reinforcement learning (RL) and multi-agent reinforcement learning (MARL) algorithms for complex decision-making problems.
• Develop scalable training pipelines using Python and modern ML frameworks.
• Build and evaluate agents in simulated environments using Gym or Petting Zoo, high-fidelity simulators, or custom environments.
• Apply RL techniques such as policy optimization, value-based learning, model-based RL, and imitation learning.
• Collaborate with domain experts to define reward structures, constraints, and evaluation metrics aligned with mission objectives.
• Implement distributed training workflows leveraging cloud compute, containerization, and orchestration technologies.
• Transition trained models into production systems, following strong software engineering best practices.
• Contribute to system architecture and performance optimization in Python with opportunities to extend into C++ or Rust for high-performance components.

Join us. The world can't wait.

• 3+ years of experience developing and training RL agents
• Experience with AI, data science, ML engineering, or software engineering
• Experience with Gym or Petting Zoo interfaces
• Experience with ML frameworks such as PyTorch, Tensor Flow, or JAX
• Experience developing technical solutions using Rust, Python, or C++
• Knowledge of RL and artificial neural networks
• Ability to travel up to 25% of the time
• Secret clearance
• Bachelor's degree in a CS, AI, or Engineering field

• Experience applying RL to autonomy, control systems, or mission-scale
• Experience with MARL
• Experience with AFSIM or other high-fidelity simulation environments
• Experience with embedded systems programming in Rust, C, or C++
• Experience in GPU programming, including CUDA or RAPID
• Experience developing in-space solutions
• Knowledge of modern software design patterns, including microservice design and orchestration in Kubernetes deployment
• Master's degree in CS, AI, Engineering, or a related field

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information;
Secret clearance is required.

At Booz Allen, we celebrate your contributions, provide you with opportunities and choices, and support your total well-being. Our offerings include health, life, disability, financial, and retirement benefits, as well as paid leave, professional development, tuition assistance, work-life programs, and dependent care. Our recognition awards program acknowledges employees for exceptional performance and superior demonstration of our values. Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible to participate in Booz Allen's benefit programs.

Individuals that do not meet the threshold are only eligible for select offerings, not inclusive of health benefits. We encourage you to learn more about our total benefits by visiting the Resource page on our Careers site and reviewing Our Employee Benefits page.

Salary at Booz Allen is determined by various factors, including but not limited to location, the individual's particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and…