2027 Internship Behavior ML Engineer, Learned Manipulation Policies

At Bedrock were moving AI out of the lab and into the real world. Our team includes veterans who helped launch Waymo scaled Segment to a $3.2B acquisition and grew Uber Freight to $5B in revenue. Today were deploying autonomous systems on heavy construction equipment across the country improving safety on job sites and accelerating schedules on critical infrastructure projects.

Were not here debating the future of AI. Were deploying it in the real just two years weve raised $350M and achieved the first fully autonomous excavator deployments in construction.

This is where algorithms meet steel-toed boots. Youll work alongside construction veterans and world-class engineers to solve physical-world problems that simulations cant touch. If youre ready to do meaningful work on hard problems wed love to have you join us.

Teaching a 40-ton excavator to move like an expert operator is a very different problem from teaching a car to stay in its lane. The motions are multimodal there are many good ways to swing dig and dump and the consequences of getting them wrong are measured in cubic yards and bent steel. Bedrocks Behavior ML team builds the learned policies that decide what our machines actually do and diffusion policies are a central bet: models that can represent the full distribution of expert behavior instead of averaging it into mush. As our Behavior ML intern youll help train those policies and build the evaluation that tells us whether theyre genuinely better working alongside two hosts who sit on both the training and evaluation sides of the problem.

• Train and iterate on diffusion flow matching and related behavior policies using real fleet demonstration data and simulated rollouts

• Run architecture conditioning and hyperparameter explorations and turn the results into clear findings the team can build on

• Build and improve evaluation pipelines that score behavior models on task success smoothness safety margins and operator-likeness

• Investigate failure modes - distribution shift mode collapse out-of-distribution scenes and propose fixes

• Work with the simulation and eval teams to make sure offline metrics actually predict on-machine performance

• Contribute to the shared training codebase with clean reviewed reproducible work

• Share results regularly with the behavior controls and autonomy teams

• Currently pursuing a BS MS or PhD in computer science robotics machine learning or a related field or bringing equivalent research or industry experience

• Strong Python and hands-on experience training models in PyTorch (or equivalent)

• Working understanding of generative modeling diffusion models flow matching VAEs or similar and of imitation learning or behavior cloning

• Experience running and interpreting real training experiments: you know how to tell a real improvement from noise

• Clear communication you can explain what you tried what happened and what youd do next

• Published work or substantial project experience in diffusion flow matching robot learning or imitation learning

• Experience training and building Vision Language Action (VLA) models

• Experience training Reinforcement Learning (RL) policies for robot manipulation

• Experience evaluating policies in simulation and reasoning about the sim-to-real gap

• Familiarity with large-scale training infrastructure and experiment tracking tooling

• Exposure to robotics autonomous vehicles or other physical-world control problems

• Interest in construction earthwork or heavy equipment - no prior experience required

Bedrock Robotics is an Equal Opportunity Employer

Were committed to building a diverse and inclusive workplace. We consider all qualified applicants for employment without regard to race color religion sex sexual orientation gender identity national origin ancestry age disability veteran status genetic information or any other protected characteristic.

Reasonable Accommodations

We want our hiring process to be accessible to everyone. If you need an accommodation to participate in the application or interview process please let your recruiter know so we can support you.

Required Experience:

Intern