Reinforcement Learning AI Engineer

Reinforcement Learning AI Engineer

Booz Allen Hamilton is seeking an innovative and experienced AI Developer specializing in Reinforcement Learning to join our growing team for Space solutions. In this role, you will leverage your expertise in artificial intelligence, data science, and machine learning engineering to train, test, deploy, and maintain models that learn from data.

• 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 Gymnasium, 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.

• 5+ years of experience in artificial intelligence, data science, machine learning engineering, or software engineering
• Experience in developing and training reinforcement learning agents
• Experience with developing technical solutions using Python, C++, or Rust
• Knowledge of machine learning, with a focus on reinforcement learning
• Ability to obtain a Secret clearance
• Bachelor's degree in a Computer Science, Artificial Intelligence, or Engineering field

• Experience applying RL to autonomy, control systems, or mission-scale
• Experience with Multi-Agent Reinforcement Learning (MARL)
• Experience with Gym or Gymnasium environments
• Experience with AFSIM or other high-fidelity simulation environments
• Experience with embedded systems programming in C, C++, or Rust
• Experience in GPU programming, including CUDA or RAPID
• Experience with ML frameworks such as PyTorch, Tensor Flow, or JAX
• Experience with developing in-space solutions
• Knowledge of modern software design patterns, including microservice design and orchestration in Kubernetes deployment
• Master's degree in Computer Science, Artificial Intelligence, 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.

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 the “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 organizational requirements.

The projected compensation range for this position is $77,500.00 to $ (annualized USD). The estimate displayed represents the typical salary range for this position and is just one component of Booz Allen’s total compensation package for employees. This posting will close within 90 days from the Posting Date.

As part of the application process, you are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.

• If this position is listed as remote or hybrid, you’ll periodically work from a Booz Allen or client site facility.
• If this position is listed as onsite, you’ll work with colleagues and clients in person, as needed for the specific role.

All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.