Research Scientist

What you’ll do Design and develop robot autonomy software stack and algorithms to enable capabilities including grasping and more dexterous behaviors in unstructured environments Research and implement state-of-the-art robot learning policies, including reinforcement learning and imitation learning-based techniques Build reliable, high-speed robot autonomy software stack optimized for inference performance Design and maintain robust data collection and curation pipelines for production robot fleets Optimize robot policies for distributed training at scale and real-time edge deployment Ship production quality, safety-critical software Required Qualifications Master’s/PhD degree in Computer Science, Machine Learning, Robotics, or equivalent technical discipline Deep expertise in machine learning fundamentals, reinforcement learning, and associated frameworks (PyTorch, TensorFlow, Ray, etc.) 3+ years of proven track record developing and deploying ML systems from research through production implementation Hands‑on experience with model lifecycle management including training, deployment, and maintenance in production settings Preferred Qualifications Authored or co‑authored peer‑reviewed publications in robotics or related fields Hands‑on experience designing and implementing bimanual manipulation tech stacks with imitation learning or RL-based methods Background in real‑time ML inference systems, simulation‑to‑reality transfer, or advanced reinforcement learning implementations Benefits We support publishing at top robotics/ML venues and presenting at conferences (travel + time fully covered). Advance SOTA dexterous manipulation research through novel methodologies while bridging theory & practice—real customer use‑cases with clear success criteria. Medical, dental & vision plans Daily meals stipend Expected Compensation $120,000 - $250,000 annual salary + cash and stock awards + benefits #J-18808-Ljbffr