Internship 2027 Behavior Machine Learning Engineer, World Models

1 мес. назад

СШАTraineeHybrid

machine learningpythondata analysis

Internship role to develop behavior machine learning models for autonomous construction equipment.

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

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

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. 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.
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