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 ● Advance SOTA dexterous manipulation research through novel methodologies while bridging theory & practice—real customer use-cases with clear success criteria. Required Qualifications ● PhD or MS 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). ● Medical, dental & vision plans ● Daily meals stipend Hiring Process ● Phone screen + 3 virtual technical interviews + onsite Expected Compensation ● $150,000 - $250,000 annual salary + cash and stock awards + benefits ● The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended. #J-18808-Ljbffr