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Postdoctoral In Reinforcement Learning Jobs (NOW HIRING)

Dexmate

Reinforcement learning engineer

Santa Clara, CA · On-site

Responsibilities : • Design and implement reinforcement learning algorithms for various robotics tasks • Develop and optimize RL training pipelines in both simulation and real-world environments ...

JazzX AI

Senior Staff AI Engineer

Los Altos, CA · On-site

$123.60K - $169.70K/yr

Required : • 10+ years of experience in AI/ML engineering, including at least 5 years specializing in reinforcement learning research and production systems. • Demonstrated success in designing ...

Virginia Tech

Postdoctoral Associate

Blacksburg, VA

Postdoctoral Associate Apply now Back to search results Job no: 534769 Work type: Research Faculty ... Expertise in reinforcement learning and/or tensor networks are preferred. Other responsibilities ...

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How much do postdoctoral in reinforcement learning jobs pay per year?

As of May 31, 2026, the average yearly pay for postdoctoral in reinforcement learning in the United States is $59,022.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,000.00 and $66,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Postdoctoral Researcher in Reinforcement Learning, and why are they important?

To thrive as a Postdoctoral Researcher in Reinforcement Learning, you need a PhD in computer science or a related field, with deep expertise in machine learning, statistics, and algorithm development. Proficiency in programming languages such as Python, experience with deep learning frameworks (e.g., TensorFlow or PyTorch), and familiarity with reinforcement learning libraries are typically required. Strong analytical thinking, problem-solving ability, collaboration, and scientific communication skills help you excel in research teams and publish impactful work. These competencies are vital to advancing state-of-the-art research, developing novel algorithms, and contributing to the academic and industrial progress in AI.

What are some common challenges faced by postdoctoral researchers in reinforcement learning, and how can they be addressed?

Postdoctoral researchers in reinforcement learning often face challenges such as balancing independent research projects with collaborative work, staying up-to-date with rapidly evolving literature, and managing the pressure to publish in top conferences. Effective time management, regular engagement with the research community through seminars and workshops, and seeking mentorship from senior colleagues can help address these challenges. Additionally, collaborating with interdisciplinary teams can offer fresh perspectives and support, making it easier to navigate complex research problems.

What is a Postdoctoral Researcher in Reinforcement Learning?

A Postdoctoral Researcher in Reinforcement Learning is an individual who has completed a PhD and conducts advanced research in the field of reinforcement learning, a branch of artificial intelligence focused on how agents take actions in environments to maximize rewards. These researchers often work in academic, industrial, or governmental research settings, collaborating on projects that advance the theoretical foundations or practical applications of reinforcement learning. Their responsibilities may include designing experiments, developing algorithms, publishing papers, and mentoring graduate students.

What is the difference between Postdoctoral In Reinforcement Learning vs Postdoctoral In Machine Learning?

AspectPostdoctoral In Reinforcement LearningPostdoctoral In Machine Learning
Required CredentialsPhD in Computer Science, AI, or related field; strong programming skills; research experience in reinforcement learningPhD in Computer Science, AI, or related field; strong programming skills; research experience in machine learning
Work EnvironmentAcademic labs, research institutions, industry R&D teams focused on reinforcement learning applicationsAcademic labs, research institutions, industry R&D teams working on various machine learning techniques
Industry UsagePrimarily in AI research, robotics, gaming, and autonomous systemsBroader applications including data analysis, predictive modeling, and AI research

Postdoctoral In Reinforcement Learning specializes in research related to decision-making algorithms and autonomous systems, whereas Postdoctoral In Machine Learning covers a wider range of AI techniques. Both roles require similar credentials but differ in focus and application areas.

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Postdoctoral In Reinforcement Learning jobs near you
Infographic showing various Postdoctoral In Reinforcement Learning job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, and 99% Full Time. Highlights an 94% Physical, and 6% Remote job distribution, with an average salary of $59,022 per year, or $28.4 per hour.
Research Scientist, Reinforcement Learning - Atlas

Research Scientist, Reinforcement Learning - Atlas

Boston Dynamics

Waltham, MA • On-site

$175K - $230K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 5 days ago

Job description

At Boston Dynamics, we are pushing the boundaries of what advanced humanoid robots can do in the real world. The Atlas team is building next-generation whole-body mobile manipulation capabilities, and we are seeking a curious, driven Research Scientist to develop cutting-edge reinforcement learning (RL) solutions that run directly on our humanoid platforms.
In this role, you will design, train, and deploy RL policies that combine whole-body movement and dexterous manipulation to solve complex tasks in unstructured environments. You'll work with a world-class team of roboticists and have rare, direct access to our physical Atlas robots and large-scale simulation infrastructure.
What You'll Do
  • Design, implement, and train reinforcement learning algorithms for challenging whole-body mobile manipulation and bimanual manipulation tasks.
  • Develop high-quality Python and C++ code that is tested, documented, and production-ready.
  • Build and leverage high-fidelity simulation environments (e.g., Isaac Sim, MuJoCo) to validate RL policies before deploying on hardware.
  • Integrate learned policies with Atlas's control and software stack through close collaboration with controls and platform teams.
  • Deploy, debug, and iterate policies directly on real Atlas hardware through hands-on experimentation.
  • Participate in design reviews, experimental planning, and team-wide research direction.

We're Looking For
  • MS or PhD in Computer Science, Machine Learning, Robotics, or a related field.
  • Strong experience training and deploying RL policies for complex behaviors in robots or simulated agents.
  • Proficiency with modern ML frameworks (e.g., PyTorch, TensorFlow, RLlib).
  • Strong foundations in algorithms, debugging, performance optimization, and robotics fundamentals (kinematics, dynamics).
  • Excellent Python and C++ programming skills and experience contributing to production-scale software.

Nice to Have
  • PhD or equivalent research experience in reinforcement learning or robotic manipulation.
  • Experience deploying RL policies on physical robots.
  • Experience developing locomotion, bimanual manipulation, or whole-body control behaviors.
  • Contributions to large software projects or open-source ML/robotics frameworks.
  • Publications in top-tier robotics or ML conferences (e.g., CoRL, RSS, ICRA, NeurIPS).

Why Join Us
  • Direct access to cutting-edge humanoid robots and the infrastructure to run large-scale RL experiments.
  • A highly collaborative, mission-driven team where your work has immediate impact.
  • The opportunity to define state-of-the-art humanoid capabilities and shape the future of real-world robotics.

The base pay range for this position is between $175,000 to $230,000 annually. Base pay will depend on multiple individualized factors including, but not limited to internal equity, job related knowledge, skills and experience. This range represents a good faith estimate of compensation at the time of posting. Boston Dynamics offers a generous Benefits package including medical, dental vision, 401(k), paid time off and a annual bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer for employment. We are growing rapidly, building a commercial company that delivers cutting edge technology and solutions to our customers from industrial applications to logistics and warehouse solutions.

Apply