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Reinforcement Learning Robotics Jobs in Boston, MA

Amazon

Applied Scientist II, Reinforcement Learning

Reading, MA · On-site

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We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control ... learning and reinforcement learning for whole-body control - Experience with methods such as ...

Tutor

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 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 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 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 Boston, MA?

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

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The top searched job categories for Reinforcement Learning Robotics jobs in Boston, MA are:

What cities near Boston, MA are hiring for Reinforcement Learning Robotics jobs?

Cities near Boston, MA with the most Reinforcement Learning Robotics job openings:

Reinforcement Learning Robotics jobs near you

Research Scientist, Reinforcement Learning - Atlas

Boston Dynamics

Waltham, MA • On-site

Full-time

Re-posted 20 days ago

Job description

Job Summary:
Boston Dynamics is pushing the boundaries of what advanced humanoid robots can do in the real world, and they are seeking a curious, driven Research Scientist to develop cutting-edge reinforcement learning solutions. The role involves designing, training, and deploying RL policies for complex tasks in unstructured environments while collaborating with a world-class team of roboticists.
Responsibilities:
• 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.
Qualifications:
Required:
• 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.
Preferred:
• 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).
Company:
Boston Dynamics is an engineering company that specializes in building dynamic robots and software for human simulation. It is a sub-organization of Hyundai Motor Company. Founded in 1992, the company is headquartered in Waltham, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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