Research Scientist, Robotics & World Models

What you'll do

• Define data specifications and training mixes for robot foundation models, and guide real-world and synthetic data collection.
• Develop benchmarks and evaluations for model quality, robustness, and real-world transfer; run fine-tuning, ablations, and scaling studies.
• Publish research and coordinate with capture, annotation, and synthetic-data teams to operationalize data plans.

What they ask for

• Bachelor’s degree in computer science, electrical engineering, robotics, or a related technical field.
• Roughly 4+ years of hands-on industry experience in robot learning or robotics ML; stated alternatives include a PhD with a compelling, current research agenda or very senior candidates with the right background.
• Hands-on experience training and evaluating robot policies using imitation learning or reinforcement learning, with strong PyTorch fundamentals.
• Experience curating robot data across embodiments and sensors, robotics data formats and standards, and simulation or synthetic data including domain randomization, system identification, and sim-to-real transfer.

Nice to have

• Advanced degree (MS or PhD) in a relevant field.
• Experience with teleoperation or egocentric data collection, adapting VLM backbones for control, fine-tuning large VLA models, or responsible-AI evaluation and red-teaming.

Pay

$160,000 - $185,000 p/year (USD, base salary)

Tools

PyTorch, LeRobot, RLDS, Open X-Embodiment, NVIDIA Isaac Sim, Isaac Lab, Omniverse, MuJoCo

AI focus

Robotics foundation models, including vision-language-action models, world models, and manipulation and locomotion policies; research on training data, evaluation, robustness, and real-world transfer.