2027 Internship State Estimation, Learned Mapping & Semantic SLAM

At Bedrock were 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 were deploying autonomous systems on heavy construction equipment across the country improving safety on job sites and accelerating schedules on critical infrastructure projects.

Were not here debating the future of AI. Were deploying it in the real just two years weve raised $350M and achieved the first fully autonomous excavator deployments in construction.

This is where algorithms meet steel-toed boots. Youll work alongside construction veterans and world-class engineers to solve physical-world problems that simulations cant touch. If youre ready to do meaningful work on hard problems wed love to have you join us.

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 youll 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. Youll test your ideas on real fleet data measure them against strong classical baselines and deliver a prototype the team can build on.

• Prototype learned SLAM and mapping methods such as place recognition odometry depth completion and neural occupancy or surface representations

• Fuse lidar and camera segmentation into consistent 3D semantic maps potentially using vision foundation models or open-vocabulary segmentation

• Develop methods that handle changing terrain moving material sparse returns dust occlusion and perceptual aliasing

• Train models on fleet lidar and camera data and build evaluation pipelines to compare mapping and localization performance against existing methods and ground truth

• Work with perception and planning teams to identify the map properties that matter most for downstream decisions

• Deliver a documented prototype experimental results and recommendations for future work

• Pursuing a BS MS or PhD in computer science robotics electrical engineering or a related field or equivalent research or industry experience

• Strong Python skills and hands-on model training experience with PyTorch or a similar framework

• Solid understanding of 3D geometry coordinate frames and transforms

• Familiarity with SLAM and mapping fundamentals point clouds or depth data

• Comfort with messy sensor data and designing experiments that distinguish real improvements from noise

• Research or project experience in learned SLAM semantic mapping or 3D scene understanding

• Experience with neural scene representations such as NeRFs 3D Gaussian splatting neural occupancy or signed distance fields

• Experience applying vision foundation models such as DINOv2 or SAM to 3D or robotics problems

• Experience with lidar processing or multi-sensor fusion

• Exposure to autonomous vehicle off-road or field robotics data

• Familiarity with Rust or C and ROS or similar robotics middleware

Bedrock Robotics is an Equal Opportunity Employer

Were 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.

Required Experience:

Intern