Robotics Research Scientist — Real-World Robot Learning

Tutor Intelligence, Inc.; San Francisco (CA); On-site; USD 180,000 - 420,000; Full time

Benefits offered by this job

Fully employer-covered health

Managed 401(k)

Unlimited PTO & holidays off

In-office meals

Job summary

Tutor Intelligence, Inc. is advancing robotics research, deploying capable robot hardware and AI to extend what robots can do in real-world settings. The research team has access to extensive robots, teleoperators, and scaling infrastructure to collect data and train models at scale, driving end-to-end AI-enabled robot products.

You will help define how our robots learn, set directions, and collaborate with applied teams to turn novel techniques into deployed models on Cassie and Sonny platforms.

Qualifications

• 5+ years of research experience in robot learning, ML, or a related field.
• Track record of original work in robot learning, imitation learning, reinforcement learning, or large-model training.
• Strong Python and hands-on experience with PyTorch or JAX.
• Experience running experiments on physical robots, not only in simulation.
• Clear communication of results, including the negative ones.

Responsibilities

• Set research directions in robot learning for dexterous manipulation.
• Develop methods that learn from large-scale human supervision: teleoperation, interventions, and rewards.
• Design experiments across the DF1 fleet and build evaluations to distinguish true improvements from noise.
• Train and post-train vision-language-action models with behavior cloning, supervised fine-tuning, and RL.
• Collaborate with researchers and engineers to deploy new techniques on Cassie and Sonny robots.
• Share results through internal reports and write-ups.

Skills

Robot learning

Python

PyTorch/JAX

Communication

Real-robot experiments

Education

PhD or equivalent

Tools

PyTorch

JAX

Job description

Tutor Intelligence, Inc. is advancing robotics research, deploying capable robot hardware and AI to extend what robots can do in real-world settings. The research team has access to extensive robots, teleoperators, and scaling infrastructure to collect data and train models at scale, driving end-to-end AI-enabled robot products.

You will help define how our robots learn, set directions, and collaborate with applied teams to turn novel techniques into deployed models on Cassie and Sonny platforms.