About the role
Putting an autonomous 40-ton excavator on a live jobsite means being able to say, precisely, what we know about its safety and what that knowledge rests on. Today that argument lives in hazard analyses, requirements, tests and logs, linked by hand.
What they're looking for
- Hands-on experience with Lean and mathlib experience, particularly real analysis or probability
- Working knowledge of probability and statistics (distributions, confidence intervals, tail bounds)
- Familiarity with knowledge graphs or structured document analysis
- Ability to translate informal claims into precise specifications and identify their assumptions
- Experience evaluating LLM-generated code or proofs
- Background in autonomous vehicles, heavy equipment, or other safety-critical robotics
More about this role
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.
Putting an autonomous 40-ton excavator on a live jobsite means being able to say, precisely, what we know about its safety and what that knowledge rests on. Today that argument lives in hazard analyses, requirements, tests and logs, linked by hand.
As a Safety Engineering intern, you’ll explore how formal methods and LLM-assisted proving can...
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