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 enabling our robots to understand and interact with the 3D world around them. We are seeking a talented Research Scientist to join our Atlas Controls team and pioneer new methods at the intersection of 3D perception and reinforcement learning.
As a Robotics Research Scientist, you will be at the heart of solving one of the most challenging problems in robotics: teaching a humanoid robot to perform complex loco-manipulation tasks in unstructured environments. Your work will focus on developing novel reinforcement learning policies that navigate and interact with the world. This is a unique opportunity to translate cutting-edge research into real-world capabilities on one of the world's most advanced robots.
What You'll Do:
Design and implement novel reinforcement learning algorithms that leverage environmental perception to solve complex locomotion and manipulation tasks on real world humanoid robots.
Leverage high-fidelity simulation environments extensively to develop and validate control policies before deploying them on physical hardware.
Collaborate closely with controls, perception, and software teams to integrate your policies into the broader robot software stack.
We're Looking For:
Ph.D. in Robotics, CS, or a related field with a focus on developing and training reinforcement learning policies for legged robot locomotion or manipulation; OR a Master's degree with 3+ years of hands-on professional experience deploying RL policies on legged robots or robotic manipulators.
Technical understanding of 3D geometry, computer vision, and data structures for representing 3D scenes.
Extensive experience developing and testing RL agents in simulation environments (e.g., Isaac Sim, MuJoCo).
Strong proficiency in Python and C++.
A solid understanding of robotics fundamentals, including kinematics, dynamics, and coordinate frames.
Nice-to-have:
Demonstrated experience deploying RL policies on physical robotic systems.
Experience integrating rich perceptual data (e.g., vision, depth) into a control or learning-based 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).
Top Skills
What We Do
Boston Dynamics builds advanced mobile manipulation robots with remarkable mobility, dexterity perception and agility. We use sensor-based controls and computation to unlock the potential of complex mechanisms. Our world-class development teams develop prototypes for wild new concepts, do build-test-build engineering and field testing and transform successful designs into robot products. Our goal is to change your idea of what robots can do.
