Job description

Reinforcement Learning AI Engineer The Opportunity: Are you an innovative and experience d artifi cia l intelligence ( AI ) developer spe cia lizing 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. What You ll Work On: 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 PettingZoo, 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 met rics aligned with mission objectives. Implement distributed training workflows leveraging cloud compute, containerization, and orchestration technologies. Transition trained models into production systems, following strong sof tware engineering best practices. Contribute to system architecture and performance optimization in Python with opportunities to extend into C or Rus t for high-performance components. Join us. The world can’t wait. You Have: 3 years of experience developing and training RL agents Experience with AI, data science, ML engineering, or sof tware engineering Experience with Gym or PettingZoo interfaces Experience with ML frameworks such as PyTorch, TensorFlow, or JAX Experience developing technical solutions using Rus t, Python, or C Knowledge of RL and artifi cia l neural networks Secret clearance Bachelor s degree in a CS, AI, or Engineering field Nice If You Have:   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 Rus t, C, or C Experience in GPU programming, including CUDA or RAPID Experience developing in-space solutions Knowledge of modern sof tware design patterns, including microservice design and orchestration in Kubernetes deployment TS/SCI clearance Master’s degree in CS, AI, Engineering, or a related field Clearance: 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. Compensation 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 organizational requirements. The projected compensation range for this position is $99,000.00 to $225,000.00 (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. Identity Statement As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. 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. Candidate AI Usage Policy AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. However, we want to ensure a fair candidate process based on your own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) or other tools to assist with responses during interviews (whether in-person or virtual) is prohibited unless permission is explicitly provided . Work Model Our people-first culture prioritizes the benefits of collaboration, whether it occurs in person or virtually. To support engagement and effective communication, employees working virtually are generally expected to have their cameras on during meetings. Remote : If this position is listed as remote, there may still be occasions when you are required to work in person at a Booz Allen or customer facility. Hybrid : If this position is listed as hybrid, you will be expected to work from a Booz Allen facility frequently, in alignment with leadership expectations and the needs of the role. You may also be required to work from or visit a customer facility. Onsite : If this position is listed as onsite, work will primarily be performed at a Booz Allen office or customer facility, where employees will collaborate directly with colleagues and customers as required by the role. Commitment to Non-Discrimination 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.

Requirements

Must-haves

Reinforcement Learning AI Engineer The Opportunity:
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 PettingZoo, 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 met rics aligned with mission objectives.
Implement distributed training workflows leveraging cloud compute, containerization, and orchestration technologies.
Transition trained models into production systems, following strong sof tware engineering best practices.
Contribute to system architecture and performance optimization in Python with opportunities to extend into C or Rus t 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 sof tware engineering
Experience with Gym or PettingZoo interfaces
Experience with ML frameworks such as PyTorch, TensorFlow, or JAX
Experience developing technical solutions using Rus t, Python, or C
Knowledge of RL and artifi cia l neural networks
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 Rus t, C, or C
Experience in GPU programming, including CUDA or RAPID
Experience developing in-space solutions

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningmlpythonkubernetes

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Professional Development