Chewy Robotics is seeking a Staff Roboticist to lead the creation and deployment of robotic systems and AI algorithms that enable bi-manual manipulation of heavy deformables, touch-augmented vision-language-action (VLA) model training, and whole-body control and reinforcement learning for humanoid robots, advancing Chewy's efforts to build the next generation of physical AI.
Requirements
- Deep expertise in robot dynamics, control, and motion planning, including model predictive control (MPC), impedance/admittance control, or whole-body control
- Demonstrated experience with reinforcement learning, simulation-to-reality transfer, or learning-based control
- Strong software background in C/C++, Python, and ROS/ROS2, with experience in real-time control and embedded systems
- Proficiency with modern robotics simulation tools (Isaac Sim, Gazebo, Mujoco) and learning platforms (Isaac Lab, Gym)
- Experience using MATLAB/Simulink for system modeling, control design, and signal processing
- Familiarity with estimation algorithms such as Kalman and particle filters, SLAM frameworks, and sensor fusion methods for localization and perception
- Working knowledge of image processing techniques, digital filter design, and signal processing
Responsibilities
- Lead the research, design, and development of control architectures for humanoid and multi-agent robotic systems, integrating vision, force, touch, and learning-based approaches
- Develop and implement advanced algorithms for dynamic control, manipulation, and interaction with deformable objects
- Design and prototype real-time control systems, simulation pipelines, and model-based controllers for robotic platforms
- Utilize modern simulation and training environments such as Isaac Lab or Gym for robot learning, and Isaac Sim, Gazebo, or Mujoco for robotic system modeling and validation
- Collaborate with scientists to develop reinforcement learning and imitation learning pipelines for dexterous manipulation and whole-body coordination, leveraging frameworks such as PyTorch or TensorFlow
- Apply control theory and modeling tools such as MATLAB/Simulink for control system design, system identification, and validation
- Contribute to the architecture and deployment of distributed robotic systems, including communication frameworks for heterogeneous robot fleets
Other
- MS or PhD in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a related field, with 8+ years of experience in robotics R&D or advanced control systems
- Author and publish results in peer-reviewed journals and conferences, contributing to the state of the art in physical AI
- Provide technical mentorship and review designs and experiments conducted by junior engineers and research assistants
- Act as a bridge between AI, mechanical, electrical, and controls disciplines, ensuring that integrated systems perform reliably and are grounded in sound engineering principles
- Strong communication and leadership skills with the ability to influence teams and articulate a broad technical vision
