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Reinforcement Learning Optimization Jobs (NOW HIRING)

Senior Reinforcement Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

Experience building or utilizing large-scale, distributed training pipelines and a strong intuition for their optimization. * A strong theoretical understanding of modern reinforcement learning ...

Applied Reinforcement Learning Engineer Location: Palo Alto, CA or Seattle, WA (Hybrid/Remote ... DPO, IPO, KTO, offline preference optimization • Group-based methods: GRPO, RLOO, sample ...

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Reinforcement Learning Optimization information

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$11K

$83.9K

$140K

How much do reinforcement learning optimization jobs pay per year?

As of Jun 7, 2026, the average yearly pay for reinforcement learning optimization in the United States is $83,885.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,000.00 and $139,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by professionals in Reinforcement Learning Optimization roles, and how can they be addressed?

Professionals in Reinforcement Learning Optimization often encounter challenges such as sparse or delayed rewards, high computational requirements, and difficulty in ensuring model stability during training. Addressing these issues typically involves leveraging techniques like reward shaping, using experience replay buffers, and adopting robust exploration strategies. Collaborating closely with data engineers, software developers, and domain experts is also crucial to ensure that the RL models are well-integrated and perform reliably in production environments.

What are the key skills and qualifications needed to thrive as a Reinforcement Learning Optimization Specialist, and why are they important?

To thrive in Reinforcement Learning Optimization, a strong background in mathematics, probability theory, machine learning algorithms, and programming (often Python) is essential, typically supported by an advanced degree in computer science or a related field. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), experience with RL libraries (like OpenAI Gym), and knowledge of optimization techniques are highly valued. Analytical thinking, problem-solving skills, and effective communication set top performers apart in this role. These capabilities are crucial for developing, fine-tuning, and deploying RL models that solve complex, real-world problems efficiently.

What is Reinforcement Learning Optimization?

Reinforcement Learning Optimization is a process in machine learning where agents learn to make decisions by interacting with an environment to achieve a specific goal. Through trial and error, the agent receives feedback in the form of rewards or penalties, which it uses to refine its actions over time. This optimization technique is widely used in robotics, gaming, and autonomous systems to develop intelligent behaviors. The core idea is to maximize cumulative rewards by finding the best sequence of decisions. Reinforcement Learning Optimization combines elements of computer science, mathematics, and statistics to solve complex real-world problems.
Reinforcement Learning AI Engineer with Security Clearance

Reinforcement Learning AI Engineer with Security Clearance

Booz Allen Hamilton

Colorado Springs, CO

$99K - $225K/yr

Other

Medical, Life, Retirement, PTO

Posted 27 days ago


Booz Allen Hamilton rating

8.8

Company rating: 8.8 out of 10

Based on 47 frontline employees who took The Breakroom Quiz

9th of 57 rated business consultants


Job description

Job Number: R0237547 Reinforcement Learning AI Engineer The Opportunity : Booz Allen is seeking an innovative and experience d AI developer spe cia lizing in reinforcement learning to join our growing team for Space solutions. In this role, you will leverage your expertise in artifi cia l intelligence, data science, and machine learning engineering to train, test, deploy, and maintain models that learn from data. You will collaborate with cross-functional teams to translate reinforcement learning research into operational capability and production-grade code, bringing significant technological advancements that drive mission success. You'll pioneer a growing community of machine learning engineers across the company. You'll collaborate with a team of dedicated Space, Military, Intelligence, Engineering, and AI professionals to deliver bleeding-edge solutions to solve high-priority national defense problems. 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 re war d 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 t war e 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: * Experience developing and training reinforcement learning agents
* Experience with Gym or PettingZoo interfaces
* Experience with ML frameworks such as PyTorch, TensorFlow, or JAX
* Experience with artifi cia l intelligence, data science, machine learning engineering, or sof t war e engineering
* Experience developing technical solutions using Python, C++, or Rus t
* Knowledge of reinforcement learning and artifi cia l neural networks
* Secret clearance
* Bachelor's degree in a Computer Science, Artifi cia l Intelligence, or Engineering field Nice If You Have: * Experience applying RL to autonomy, control systems, or mission-scale
* Experience with Multi-Agent Reinforcement Learning ( MARL )
* Experience with AFSIM or other high-fidelity simulation environments
* Experience with embedded systems programming in C, C++, or Rus t
* Experience in GPU programming, including CUDA or RAPID
* Experience developing in-space solutions
* Knowledge of modern sof t war e design patterns, including microservice design and orchestration in Kubernetes deployment
* Master's degree in Computer Science, Artifi cia l Intelligence, 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.

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About Booz Allen Hamilton

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Booz Allen Hamilton is a leading provider of management and technology consulting services to the US government in defense, intelligence, and civil markets. Headquartered in McLean, Virginia, the firm also serves major corporations, institutions, and not-for-profit organizations. Founded in 1914 by Edwin G. Booz, the company has a long-standing tradition of helping clients achieve success by delivering a wide range of consulting services that include strategic planning, human capital and learning, communication, systems development, and others. The company's mission is to empower people to change the world, and it has a reputation for maintaining the highest standards of integrity and-excellence.

Industry

It services

Company size

10,000+ Employees

Headquarters location

McLean, VA, US

Year founded

1914