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Reinforcement Learning Robotics Jobs in Massachusetts

Eka

Machine Learning / Computer Vision Engineer

Boston, MA · On-site

$100 - $125/hr

Develop visual models that support reinforcement learning and imitation learning policies, including end‑to‑end visuomotor policies that map visual observations to robot actions. * Improve our ...

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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.

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Reinforcement Learning Robotics jobs near you

Internship - Embodied AI & Humanoid Robotics

Mitsubishi Electric Research Laboratories

Cambridge, MA • On-site

Full-time, Internship

Medical

Re-posted 2 days ago

Job description

Join our cutting-edge research team to help advance the next generation of Embodied AI and Humanoid Robotics. As a research intern, you will develop AI technologies that enable humanoid robots to understand, reason, and interact with the physical world through complex manipulation, assembly, and tool-use tasks. This is a unique opportunity to contribute to impactful research with the goal of publishing at leading AI and robotics conferences.

What You'll Work On

Depending on your background and interests, projects may include:

  • Embodied AI for dexterous manipulation, assembly, and tool use
  • Vision-Language-Action (VLA) models and Foundation Models for robotic control
  • World-Action Models (WAM) for long-horizon planning and decision making
  • Learning from human demonstrations, teleoperation, and autonomous data collection
  • Sim-to-real transfer, reinforcement learning, and real-world robot deployment
What We're Looking For

We are seeking highly motivated graduate students with:

  • Strong research experience in robotics, embodied AI, machine learning, computer vision, or related fields
  • Experience with deep learning frameworks such as PyTorch or JAX, and strong Python programming skills
  • Familiarity with one or more of the following:
    • Vision-Language-Action (VLA) models
    • Foundation Models or multimodal AI
    • Reinforcement learning or imitation learning
    • Robot manipulation, motion planning, or control
    • Agentic AI systems for robotics

Preferred qualifications:

  • Hands-on experience with humanoid or loco manipulators (e.g., Unitree G1)
  • Experience with teleoperation systems (e.g., Pico, Sonic)
  • Experience with robotics simulators (e.g., Isaac Sim, MuJoCo, Genesis)
  • Familiarity with ROS/ROS 2 and real-world robot experimentation
  • Familiarity with policy deployment on edge AI devices (e.g., Jetson GPUs)
Internship Details
  • Duration: Approximately 4 months
  • Start Date: Flexible
  • Location: Cambridge, MA
  • Objective: Conduct high-impact research leading to publications at premier AI and robotics conferences (e.g., CoRL, RSS, ICRA, IROS, NeurIPS, ICML)

If you are excited about building AI that enables robots to perform complex real-world tasksincluding assembly, tool use, and dexterous manipulationwe encourage you to apply.

The pay range for this internship position will be 6-8K per month.

Mitsubishi Electric Research Labs, Inc. "MERL" provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, MERL complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

MERL expressly prohibits any form of workplace harassment based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. Improper interference with the ability of MERLs employees to perform their job duties may result in discipline up to and including discharge.

Working at MERL requires full authorization to work in the U.S and access to technology, software and other information that is subject to governmental access control restrictions, due to export controls. Employment is conditioned on continued full authorization to work in the U.S and the availability of government authorization for the release of these items, which might include without limitation, obtaining an export license or other documentation. MERL may delay commencement of employment, rescind an offer of employment, terminate employment, and/or modify job responsibilities, compensation, benefits, and/or access to MERL facilities and information systems, as MERL deems appropriate, to ensure practical compliance with applicable employment law and government access control restrictions.

In addition to base pay, interns receive a relocation stipend, covered travel to and from MERL, and a monthly Charlie Card for local commuting. Interns are invited to participate in weekly social gatherings and professional development opportunities, including research talks by both internal and external speakers. Interns who meet the 90-day waiting period are also eligible for health insurance coverage. MERL provides immigration support for qualified candidates as needed. Employment is considered at-will, and the Company reserves the right to modify base salary or any other compensation program at any time, including for reasons related to individual performance, departmental or Company performance, and market conditions.

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