Product Intern

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.

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.

About the Role & Team

Bedrock's Product team decides what our autonomous machines should learn to do next. We also make sure the people who work alongside them get real value from them: operators, site managers and the construction companies we partner with. Our problems rarely arrive as specs. Which task or machine type is worth taking on next? How do you turn "digs like an expert" into a number you can measure? What does a partner need to see before trusting a 40-ton machine on their site?

As our Product intern, you'll get a problem like that, not a task list, and own it for the summer. You'll frame it, work out the answer, build what's needed, and bring the team a recommendation they can act on. You'll work the way our team does: with AI tools in hand, going from question to working prototype in days, not weeks.

What You'll Do

• Own an open product problem end to end: frame it, find the data and the people who know, decide what to build, and ship it before the summer ends

• Turn fleet data from real jobsites into decisions: how well our machines perform, where they struggle, and what that means for what we build next

• Prototype with AI coding tools and agents: internal tools, data pipelines, automated workflows, and working demos that make an idea concrete instead of slides about it

• Spend time at our field sites with operators and site teams, and turn what you see into requirements engineers can build against

• Work across autonomy, evaluation, operations and commercial teams to pressure-test ideas and unblock yourself

• Write up your findings and present a clear recommendation to leadership: what you found, what you built, and what we should do next