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.
Before an autonomous excavator digs its first trench on a new site, it's already dug thousands in simulation. The Simulation team builds the virtual environments our autonomy stack trains and tests against — and the closer sim looks and behaves like the real world, the faster we move. Neural rendering is the next step: replacing hand-authored assets and approximations with learned representations that capture the visual complexity of real jobsites — dust, lighting, deformable terrain, heavy equipment in motion. As our Simulation intern, you'll push neural rendering techniques into our sim pipeline and measure whether they actually close the visual gap that matters for downstream autonomy performance.
Research, implement, and benchmark neural rendering methods (NeRF, 3D Gaussian splatting, or related techniques) for generating realistic construction-site imagery within our simulation stack
Train models on real-world site data captured by our fleet and evaluate visual fidelity, temporal consistency, and render speed
Integrate neural rendering outputs into the simulation pipeline so perception and planning teams can train and test against them
Build evaluation metrics and tooling that quantify how well rendered scenes match real fleet data — and whether that improvement transfers to autonomy performance
Identify and address failure modes: dynamic objects, deformable terrain, dust, harsh lighting, and other construction-specific challenges
Document findings, limitations, and a recommendation on where neural rendering should (and shouldn't) replace traditional sim assets
Currently pursuing a BS, MS, or PhD in computer science, computer graphics, robotics, or a related field — or bringing equivalent research or industry experience
Strong Python and hands-on experience with PyTorch (or equivalent)
Solid understanding of 3D graphics fundamentals: rendering pipelines, scene representations, camera models, and coordinate systems
Familiarity with neural scene representations (NeRF, Gaussian splatting, neural radiance fields, or related methods)
Comfort with real-world data — construction sites are messy, dusty, and nothing like an indoor dataset
Published work or substantial project experience in neural rendering, novel view synthesis, or differentiable rendering
Experience with simulation engines (Unreal, Unity, NVIDIA Isaac Sim, or similar)
Background in autonomous vehicle simulation or synthetic data generation
Familiarity with C++ and GPU programming (CUDA, OpenGL, Vulkan)
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.