Want to know if this job is worth applying to?
San Francisco, California, United States
Onsite
At Bedrock, we're moving AI out of the lab and onto real job sites. Our team includes veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue. We retrofit the heavy equipment contractors already own, starting with excavators, so experienced crews can safely take on more projects and deliver more of the critical infrastructure our society needs.
In August 2026, Bedrock-equipped excavators began doing fully autonomous, paid work on live commercial job sites. We've more than doubled our customer base since 2025, and our machines now work with contractors across the South, Midwest, and Mid-Atlantic
In October 2026, we raised a $600M Series C co-led by CapitalG and Emergence Capital, bringing our total funding to nearly $1B. We're using it to put more autonomous machines to work, build the field and operations teams behind every deployment, and expand into new machine types and job-site tasks.
This is where algorithms meet steel-toed boots. You'll work alongside construction veterans and world-class engineers to solve physical-world problems that simulations can't touch. If you're ready to do meaningful work on hard problems, we'd love to have you join us.
Predicting what happens next on a construction site is one of the hardest and most valuable problems at Bedrock, whether that's soil dynamics, machine interactions, or the people moving around the site. Every scoop of dirt we move rewrites the scene we have to plan against. The Behavior ML team is building world models that let our machines reason about the near future instead of just reacting to the present. As our intern, you'll train models on real fleet data, run architecture explorations, and work closely with the Behavior and Controls teams to ship what you build onto a real excavator.
Train and evaluate world models on real fleet data collected from autonomous machines in the field
Run architecture explorations and ablations, and make a defensible case for what's actually working
Build evaluation harnesses and metrics that tell us whether a model is genuinely better
Partner with the behavior and controls teams to connect model outputs to planning and control
Present your findings and provide a solid foundation for the team to build upon
Currently pursuing a BS, MS, or PhD in computer science, machine learning, robotics, or a related field — or bringing equivalent research or industry experience
Strong Python and hands-on experience training models in PyTorch (or equivalent)
Ability to read a paper and turn it into a working implementation
Comfort with messy, real-world data — this is not a curated benchmark
Sound experimental judgment understanding the difference between a real result and noise
Experience with world models, video prediction, or sequence modeling (e.g., DreamerV3, V-JEPA 2, Genie 3, GAIA-2, NVIDIA Cosmos, etc.)
Background in reinforcement learning or imitation learning
Prior work with robotics or autonomous vehicle data
Familiarity with large-scale training infrastructure
About This Internship
This is a fixed-term, project-based internship designed strictly for students (undergraduate or graduate) seeking resume-building experience, hands-on skill development, or industry exposure rather than a direct career launchpad. Candidates will own discrete, short-term projects that can be fully completed within the internship timeframe. Please note that while exceptional interns may occasionally be considered if business needs align, opportunities for full-time conversion are highly limited."
Bedrock Robotics is an Equal Opportunity Employer
We’re 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.
