⭐ Robotics Engineer/Researcher - Robot Learning - Imitation Learning, Foundation Models, RL

All open rolesAI⭐ Robotics Engineer/Researcher - Robot Learning - Imitation Learning, Foundation Models, RLMountain View, CA (On-Site)/Full-timeApply nowShareAbout the roleJoin our team to push the frontier of robot learning. You'll train general-purpose control policies at scale — spanning imitation learning and large multimodal models — build the data and evaluation pipelines that make them work, and take policies from training runs to real robots. We care more about your ability to train models that work than about any particular robot, task, or sensor you've used before.Requirements01MS or PhD in Robotics, Computer Science, Machine Learning, or related field—or equivalent experience02Strong track record training neural networks end-to-end: you can take a model from idea to a working, debugged, reproducible result03Experience developing robot learning policies like diffusion policies, 3D policies, vision-language-action models, or video action models04Experience training models at scale: multi-GPU/multi-node training, large datasets, long runs, and debugging throughput, stability, and scaling behavior05Strong software engineering skills in Python and PyTorch or JAX in Linux environments (C++ a plus)06Experience building data pipelines for robot learning — demonstration collection, curation, filtering, and dataset design07Rigorous about evaluation: designing benchmarks, running ablations, and drawing correct conclusions from noisy real-world results08(+) Hands-on robotics experience — hardware bring-up, teleoperation and real-world data collection, on-robot deployment09(+) Experience with high-performance simulation (MuJoCo, Isaac Gym/Lab) and sim2real techniques (domain randomization, dynamics adaptation, residual policy learning)10(+) Familiarity with contact-rich or dexterous manipulation, tactile sensing, or differentiable simulationDetails & responsibilities01Design and implement scalable training pipelines for general-purpose manipulation policies02Train large multimodal policies — diffusion, 3D, vision-language-action, and video action models — and push them to state-of-the-art performance on real tasks03Build the data engine behind the models: demonstration collection, curation, filtering, and dataset design at scale04Integrate visual, proprioceptive, and tactile feedback into policy architectures05Take policies from training runs to real hardware, closing the loop with on-robot deployment and iteration06Collaborate across AI, hardware, and perception teams to build closed-loop manipulation systems07Publish or contribute to cutting-edge research while delivering production-quality control stacksCompensation & benefits01Competitive salary and meaningful equity02Full health, dental, and vision insurance03Access to custom-built dexterous robots04Collaboration with leading researchers in robotics and AI05Backed by YC and top-tier investors06High-ownership role with the opportunity to lead core initiatives in real-world robot learningInterested in this role?Applying takes a few minutes — you'll need an account to submit.Apply now