2027 Internship Behavior Machine Learning Engineer, World Models

Join the team bringing advanced autonomy to the built world

At Bedrock, we're 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, we're deploying autonomous systems on heavy construction equipment across the country, improving safety on job sites and accelerating schedules on critical infrastructure projects.

We're not here debating the future of AI. We're deploying it in the real world. In just two years, we've raised $350M and achieved the first fully autonomous excavator deployments in construction.

About the Role & Team

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.

What You'll Do

• 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

What We're Looking For

Required

• 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

Preferred

• 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."