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Reinforcement Learning Robotics Jobs in Massachusetts

Staff Research Roboticist

Waltham, MA · On-site

$180K - $240K/yr

... reinforcement learning (RL) solutions that run directly on our robots. What You'll Do * Design, implement, train, and deploy state-of-the-art ML/RL algorithms for complex last-mile delivery ...

Staff Research Roboticist

Waltham, MA · On-site

$180K - $240K/yr

... reinforcement learning (RL) solutions that run directly on our robots. What You'll Do * Design, implement, train, and deploy state-of-the-art ML/RL algorithms for complex last-mile delivery ...

Senior Research Scientist - Manipulation

Boston, MA · On-site

$107K - $136K/yr

A strong research record in robot learning, robotic manipulation, reinforcement learning, imitation learning, multimodal learning, or a related area. * Demonstrated ability to lead research projects ...

A strong research record in robot learning, robotic manipulation, reinforcement learning, imitation learning, multimodal learning, or a related area. * Demonstrated ability to lead research projects ...

A strong research record in robot learning, robotic manipulation, reinforcement learning, imitation learning, multimodal learning, or a related area. * Demonstrated ability to lead research projects ...

Senior Robotics Software Engineer

Watertown, MA · On-site

$133K - $175K/yr

... Reinforcement learning • Proficiency programming in a Python-Linux environment • Comfort with programming linters (Flake8, Mypy) • Software support of real-time systems • Visualization of ...

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Reinforcement Learning Robotics information

What is reinforcement learning in robotics?

Reinforcement learning in robotics refers to a type of machine learning where robots learn to perform tasks through trial and error, receiving feedback from their actions in the form of rewards or penalties. This approach allows robots to autonomously develop complex behaviors by interacting with their environment, rather than relying solely on pre-programmed instructions. Reinforcement learning is especially useful for tasks that are difficult to model explicitly, such as walking, grasping, or navigation. Over time, the robot improves its performance by maximizing the cumulative reward, leading to more efficient and adaptive behaviors.

What are some common challenges faced when implementing reinforcement learning algorithms in robotics projects?

One common challenge in this role is bridging the gap between simulation and real-world environments, as algorithms that perform well in simulation may not translate directly to physical robots due to unpredictable variables and hardware limitations. Additionally, ensuring the safety and stability of the robot during training is crucial, since trial-and-error learning can sometimes result in unintended behaviors or hardware damage. Collaboration with hardware engineers and domain experts is often necessary to fine-tune models, interpret results, and iterate on solutions. Overcoming these challenges requires patience, adaptability, and strong communication skills within a multidisciplinary team.

What are the key skills and qualifications needed to thrive as a reinforcement learning robotics engineer, and why are they important?

To thrive as a Reinforcement Learning Robotics Engineer, you need a strong background in robotics, machine learning, and programming, typically supported by a degree in computer science, engineering, or a related field. Expertise with frameworks like TensorFlow or PyTorch, experience with simulation environments (such as Gazebo or ROS), and familiarity with reinforcement learning algorithms are essential. Strong problem-solving skills, creativity, and effective communication set standout professionals apart in this rapidly evolving field. These skills enable engineers to develop intelligent robotic systems that adapt and learn efficiently, driving innovation and practical deployment in real-world environments.

What is the difference between Reinforcement Learning Robotics vs Machine Learning Engineer?

AspectReinforcement Learning RoboticsMachine Learning Engineer
Required CredentialsDegree in Robotics, Computer Science, or related fields; knowledge of reinforcement learningDegree in Computer Science, Data Science, or related fields; expertise in machine learning algorithms
Work EnvironmentRobotics labs, manufacturing, autonomous systemsTech companies, data-driven projects, software development
Industry UsageAutonomous robots, industrial automation, researchData analysis, predictive modeling, AI applications

Reinforcement Learning Robotics focuses on applying reinforcement learning techniques to control and optimize robotic systems, often in physical environments. Machine Learning Engineers develop algorithms for a broad range of applications, including data analysis and predictive modeling. While both roles require knowledge of machine learning, Reinforcement Learning Robotics emphasizes robotics and real-world interaction, whereas Machine Learning Engineers work across various industries with software-based solutions.

What are popular job titles related to Reinforcement Learning Robotics jobs in Massachusetts?

For Reinforcement Learning Robotics jobs in Massachusetts, the most frequently searched job titles are:

What cities in Massachusetts are hiring for Reinforcement Learning Robotics jobs?

Cities in Massachusetts with the most Reinforcement Learning Robotics job openings:

Research Scientist, Reinforcement Learning - Atlas

Bostondynamics

Waltham, MA • On-site

$175K - $230K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 12 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.