Principal Research Scientist

About the role

The Principal Research Scientist will lead Chewy’s scientific roadmap in embodied AI and humanoid robot learning, focusing on reinforcement learning, imitation learning, vision-language-action models, and modern control approaches for real-world robotic systems.

Responsibilities

• Define and lead Chewy’s scientific roadmap for embodied AI and humanoid robot learning
• Invent, prototype, and validate novel algorithms for manipulation, loco-manipulation, whole-body coordination, multimodal perception, policy adaptation, and task generalization across environments and robot embodiments
• Develop learning systems that combine data-driven policies with principled robotics methods such as planning, control, system identification, estimation, and safety-constrained execution
• Drive advances in simulation, synthetic data generation, offline and online evaluation, benchmarking, and sim-to-real transfer to accelerate learning and reduce time to deployment
• Build and evaluate robot learning pipelines that leverage vision, language, proprioception, force, and touch to enable robust performance on complex physical tasks
• Partner with cross-functional teams to translate ambiguous business needs into tractable scientific programs, technical milestones, and experimental roadmaps
• Influence the architecture of Chewy’s physical AI stack, including model training strategy, data engines, evaluation methodology, and integration with real robot platforms
• Establish technical standards for scientific rigor, experiment design, ablation studies, reproducibility, and model evaluation across the team
• Publish, patent, and communicate high-impact work internally and externally, helping strengthen Chewy’s reputation in robotics and embodied AI
• Mentor scientists and engineers, raise the bar for technical depth and judgment, and serve as a trusted technical advisor to senior leadership

Requirements

• PhD in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, Applied Mathematics, or a related technical field
• 10+ years of relevant experience in robotics research, embodied AI, machine learning, controls, or a closely related domain
• Deep expertise in several of the following areas: reinforcement learning, imitation learning or behavior cloning, offline RL or policy improvement from logged data, vision-language-action models or embodied foundation models, robot manipulation and loco-manipulation, whole-body control, MPC, or optimization-based control, system identification, state estimation, or sensor fusion, sim-to-real transfer and domain adaptation
• Demonstrated track record of developing novel methods that improved real robot performance, not just offline benchmarks
• Strong publication, patent, and/or open-source record in top-tier robotics or machine learning venues such as CoRL, RSS, ICRA, IROS, NeurIPS, ICML, or related forums
• Strong software and research engineering skills in Python and C++, with experience in modern ML frameworks such as PyTorch and/or JAX
• Experience with robotics tooling and simulation environments such as ROS2, Isaac Lab, Isaac Sim, MuJoCo, Gazebo, or equivalent platforms
• Proven ability to operate as a top-level technical leader in ambiguous environments, influence without authority, and communicate effectively with executive stakeholders

Qualifications

• Bonus: Experience training and deploying policies on humanoid robots or other dynamically complex platforms such as legged robots or mobile manipulators
• Bonus: Experience with dexterous or force-sensitive manipulation, deformable object handling, or contact-rich tasks
• Bonus: Experience building or adapting foundation models for robotics, including multimodal representation learning or action modeling
• Bonus: Experience combining learned policies with classical controls, planners, or safety layers for production-grade systems
• Bonus: Experience working on warehouse, logistics, or industrial robotics applications
• Bonus: Experience leading external collaborations with academic labs, research partners, or strategic technical vendors