Perception Engineer

Light Speed Build Technologies is revolutionizing the construction industry through AI-powered robotics. Our flagship systems - BRUTE for automated wall panel manufacturing and DEX for on-site collaborative construction - are addressing the global housing crisis by delivering unprecedented speed, precision, and affordability in homebuilding.

As a Perception Engineer, you will own how Light Speed's robots see. You will design, calibrate, and deploy the multi-camera systems on our robot cells and end-of-arm tooling, and build the perception that guides manipulation in real time. Your camera streams also feed our teleoperation and robot learning pipelines, so the quality of what you build directly shapes how well our robots learn.

This role sits at the intersection of sensor hardware, 3D vision, and deep learning, all deployed on physical robots where reliability matters.

• Select, specify, and deploy multi-camera systems (RGB, stereo, depth) for robot cells, including wrist- and tool-mounted cameras on end-of-arm tooling and dexterous hands

• Own intrinsic, extrinsic, and hand-eye calibration, and keep calibration reliable across tool changes and daily operation

• Synchronize cameras with robot state and teleoperation streams

• Work with mechanical engineers on camera placement for coverage, occlusion, and lighting

• Estimate and track robot and end-effector pose using vision systems to verify kinematics and identify drift

• Compare 3D scans against CAD or BIM models to check part placement and as-built accuracy

• Localize robots and tools in the workspace using fiducials (April Tag or Ch Ar Uco ) and multi-view fusion

• Build object detection, segmentation, and 6-DoF pose estimation for parts, fasteners, and tools in cluttered, confined, and poorly lit work spaces

• Build point cloud pipelines (filtering, segmentation, registration such as ICP, and meshing) for manipulation and scene understanding

• Track hands and objects in egocentric video of human demonstrations

• Build CUDA-optimized perception pipelines: GPU preprocessing, custom CUDA kernels where needed, TensorRT inference, and minimal host-device copies

• Profile and optimize end-to-end latency, from photon to action, using tools like Nsight Systems

• Deliver calibrated, time-synchronized camera data in the formats our teleoperation recording and training pipelines consume

• Partner with AI/ML engineers to define observation spaces for imitation learning and vision-language-action policies

• Set perception accuracy targets tied to task success, and build benchmarks to measure them

• Integrate perception with ROS2-based robot control

• Harden systems for real-world conditions: lighting changes, reflective surfaces, occlusion, and vibration

• Collaborate closely with robotics, mechanical, and controls engineers

• 3+ years building and deploying perception systems on physical robots or real-time systems

• Hands-on experience calibrating multi-camera systems (intrinsic, extrinsic, hand-eye) and synchronizing sensors

• Experience with RGB-D and stereo cameras in real deployments

• Strong computer vision fundamentals: camera geometry, multi-view geometry, and 3D reconstruction

• Deep learning experience with detection, segmentation, or pose estimation using Py Torch

• Strong Python and C++

• Experience with OpenCV and point cloud libraries such as Open3D or PCL

• Experience with ROS or ROS2

• Proficiency with Linux, Docker, Git, and CI/CD workflows

• MS or PhD in Computer Vision, Robotics, Computer Science, or a related field

• Perception for robotic manipulation, especially dexterous or tool-based manipulation

• Experience with hardware video encoding (NVENC, Jetson Multimedia API), GStreamer, or WebRTC

• Experience with NVIDIA Isaac ROS / NITROS, VPI, or CV-CUDA

• Experience with point cloud registration and scan-to-CAD/BIM comparison

• Experience with vision foundation models (for example SAM, DINOv2, Foundation Pose)

• Experience with egocentric video or hand pose estimation

• Experience producing sensor data for robot learning datasets (e.g., rosbag or MCAP)

• Edge deployment on NVIDIA Jetson with TensorRT

• Simulation and synthetic data generation with Isaac Sim, Mu Jo Co , or similar

• Background in manufacturing, industrial automation, or construction technology

• Build the eyes of robots that are addressing the…