Senior Robotics Research Engineer

2 weeks ago

Southampton, Southampton, United Kingdom Boston Dynamics Full time £60,000 - £100,000 per year

At Boston Dynamics, we are developing the next generation of intelligent robots capable of operating in complex, human-centric environments. A critical component of this effort is creating robust, dynamic, and intelligent behaviors through advanced machine learning. We are seeking a talented Robotics Engineer to join our Atlas Controls team and help pioneer new methods in reinforcement learning for complex robotic systems.

As a Senior Robotics Research Engineer, you will be a key contributor to solving one of the most challenging problems in robotics: teaching a humanoid robot to perform complex locomotion and manipulation tasks. Your work will focus on implementing, testing, and refining reinforcement learning policies to create sophisticated and robust behaviors. This is a unique opportunity to help translate cutting-edge research into real-world capabilities on one of the world's most advanced robots.

What You'll Do:

  • Implement, train, and test reinforcement learning algorithms to create robust and dynamic locomotion and manipulation behaviors.

  • Leverage high-fidelity simulation environments to develop, validate, and debug control policies.

  • Assist in analyzing the performance of policies on the physical robot and work on sim-to-real challenges.

  • Collaborate with controls, perception, and software teams to integrate your work into the broader robot software stack.

We're Looking For:

  • Master's degree in Robotics, CS, or a related field; OR a Bachelor's degree with 2+ years of hands-on professional experience in a related area.

  • Hands-on experience developing and implementing learning algorithms for control tasks (can include significant academic, internship, or professional projects).

  • Experience with physics simulation engines (e.g., MuJoCo, Isaac Sim)

  • Proficiency in Python and familiarity with C++.

  • A solid understanding of robotics fundamentals, including kinematics, dynamics, and coordinate frames.

Nice-to-have:

  • Demonstrated experience with projects involving physical robotic systems.

  • Experience integrating perceptual data (e.g., vision, depth) into a control policy.

  • A passion for building robust and reliable software for real-world robotic systems.

  • Publication record in top-tier robotics, machine learning, or computer vision conferences (e.g., CoRL, RSS, ICRA, CVPR, NeurIPS).

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