Bedrock Robotics

<h2>Join the team bringing advanced autonomy to the built world</h2>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.<h2>About the Role &amp; Team</h2>Teaching a 40-ton excavator to move like an expert operator is a very different problem from teaching a car to stay in its lane. The motions are multimodal, there are many good ways to swing, dig, and dump and the consequences of getting them wrong are measured in cubic yards and bent steel. Bedrock's Behavior ML team builds the learned policies that decide what our machines actually do, and diffusion policies are a central bet: models that can represent the full distribution of expert behavior instead of averaging it into mush. As our Behavior ML intern, you'll help train those policies and build the evaluation that tells us whether they're genuinely better working alongside two hosts who sit on both the training and evaluation sides of the problem.<h2>What You'll Do</h2><ul><li>Train and iterate on diffusion flow matching, and related behavior policies using real fleet demonstration data and simulated rollouts</li><li>Run architecture, conditioning, and hyperparameter explorations, and turn the results into clear findings the team can build on</li><li>Build and improve evaluation pipelines that score behavior models on task success, smoothness, safety margins, and operator-likeness</li><li>Investigate failure modes - distribution shift, mode collapse, out-of-distribution scenes and propose fixes</li><li>Work with the simulation and eval teams to make sure offline metrics actually predict on-machine performance</li><li>Contribute to the shared training codebase with clean, reviewed, reproducible work</li><li>Share results regularly with the behavior, controls, and autonomy teams</li></ul><h2>What We're Looking For</h2><h3>Required</h3><ul><li>Currently pursuing a BS, MS, or PhD in computer science, robotics, machine learning, or a related field or bringing equivalent research or industry experience</li><li>Strong Python and hands-on experience training models in PyTorch (or equivalent)</li><li>Working understanding of generative modeling diffusion models, flow matching, VAEs, or similar and of imitation learning or behavior cloning</li><li>Experience running and interpreting real training experiments: you know how to tell a real improvement from noise</li><li>Clear communication, you can explain what you tried, what happened, and what you'd do next</li></ul><h3>Preferred</h3><ul><li>Published work or substantial project experience in diffusion, flow matching, robot learning, or imitation learning</li><li>Experience training and building Vision Language Action (VLA) models</li><li>Experience training Reinforcement Learning (RL) policies for robot manipulation</li><li>Experience evaluating policies in simulation and reasoning about the sim-to-real gap</li><li>Familiarity with large-scale training infrastructure and experiment tracking tooling</li><li>Exposure to robotics, autonomous vehicles, or other physical-world control problems</li><li>Interest in construction, earthwork, or heavy equipment - no prior experience required</li></ul>About This InternshipThis 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."<div> </div>Bedrock Robotics is an Equal Opportunity EmployerWe’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 AccommodationsWe 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.

2027 Internship Behavior ML Engineer, Learned Manipulation Policies

<h2>Join the team bringing advanced autonomy to the built world</h2>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.<h2>About the Role &amp; Team</h2>Construction sites change with every bucket of dirt. Our State Estimation team builds the maps and localization systems that help autonomous excavators understand where they are and how the terrain is changing.As an intern on this team, you'll explore how modern learning-based methods can improve our geometry-first mapping stack. That could mean localizing reliably in terrain that looks the same in every direction, building maps that hold up through dust and occlusion, or labeling the map semantically so the machine can tell material to dig from haul roads, spoil piles, and berms. You'll test your ideas on real fleet data, measure them against strong classical baselines, and deliver a prototype the team can build on.<h2>What You'll Do</h2><ul><li>Prototype learned SLAM and mapping methods, such as place recognition, odometry, depth completion, and neural occupancy or surface representations</li><li>Fuse lidar and camera segmentation into consistent 3D semantic maps, potentially using vision foundation models or open-vocabulary segmentation</li><li>Develop methods that handle changing terrain, moving material, sparse returns, dust, occlusion, and perceptual aliasing</li><li>Train models on fleet lidar and camera data, and build evaluation pipelines to compare mapping and localization performance against existing methods and ground truth</li><li>Work with perception and planning teams to identify the map properties that matter most for downstream decisions</li><li>Deliver a documented prototype, experimental results, and recommendations for future work</li></ul><h2>What We're Looking For</h2><h3>Required</h3><ul><li>Pursuing a BS, MS, or PhD in computer science, robotics, electrical engineering, or a related field, or equivalent research or industry experience</li><li>Strong Python skills and hands-on model training experience with PyTorch or a similar framework</li><li>Solid understanding of 3D geometry, coordinate frames, and transforms</li><li>Familiarity with SLAM and mapping fundamentals, point clouds, or depth data</li><li>Comfort with messy sensor data and designing experiments that distinguish real improvements from noise</li></ul><h3>Preferred</h3><ul><li>Research or project experience in learned SLAM, semantic mapping, or 3D scene understanding</li><li>Experience with neural scene representations, such as NeRFs, 3D Gaussian splatting, neural occupancy, or signed distance fields</li><li>Experience applying vision foundation models, such as DINOv2 or SAM, to 3D or robotics problems</li><li>Experience with lidar processing or multi-sensor fusion</li><li>Exposure to autonomous vehicle, off-road, or field robotics data</li><li>Familiarity with Rust or C++, and ROS or similar robotics middleware</li></ul>About This InternshipThis 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."<div> </div>Bedrock Robotics is an Equal Opportunity EmployerWe’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 AccommodationsWe 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.

2027 Internship State Estimation, Learned Mapping & Semantic SLAM

<h2>Join the team bringing advanced autonomy to the built world</h2>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.<h2>Machine Learning Engineer: Perception Analytics</h2>We are looking for a perception engineer to build features for our customers' analytics. This isn’t just a data science job. This is developing fundamental perception features to drive customer-facing platforms. What are the real-world challenges in measuring dig productivity from lidar/camera data? Can we modify existing perception systems to provide useful metrics for job sites? How do you measure safety over an entire site given perception systems? How do you re-identify the same objects across dozens of camera views on a site several city blocks wide, through dust and changing light?<h2>What You’ll Do:</h2><ul><li>Extend, modify and adapt existing perception signals for analytics needs</li><li>Work with customers to define and scope what is possible with advanced perception systems on-site</li><li>Deploy models and analytics directly to fleets of machines</li></ul><h2>What We're Looking For:</h2><ul><li>MSc or advanced degree in Computer Science, Robotics, or a related field</li><li>4+ years of professional experience shipping perception systems to production (ideally on robotic or other embedded platforms), with strong hands-on experience in a modeling framework (e.g. PyTorch)</li><li>Proficient in Python and comfortable reading and writing at least one systems language (e.g. C++, Rust)</li><li>Hands-on experience incorporating raw sensor data (camera, lidar, IMU) into learned pipelines</li><li>Solid grounding in 3D geometry, sensor calibration (intrinsics/extrinsics), coordinate transforms, and camera/image re-projection algorithms</li><li>Strong data analysis skills across statistical characterization of sensor data, corner-case and anomaly discovery, and evaluation design</li></ul><h2>Ways to Stand Out:</h2>One or more of the following:<ul><li>Prior experience working with customers to understand perception data and analytics</li><li>Experience with the Rust programming language</li><li>Published work in top-tier venues such as ICRA, IROS, CVPR, ECCV, ICCV, CoRL, or RSS</li></ul><h2>Other special aspects of the role:</h2><ul><li>Based in the Bay Area with the ability to be onsite at our SF office on a daily/weekly basis</li></ul>Bedrock Robotics is an Equal Opportunity EmployerWe’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 AccommodationsWe 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.

Bedrock Robotics

Open jobs at Bedrock Robotics

2027 Internship Behavior ML Engineer, Learned Manipulation Policies

2027 Internship State Estimation, Learned Mapping & Semantic SLAM

Machine Learning Engineer: Perception Analytics

Working for Bedrock Robotics?

Featured companies