Robot Perception Engineer - Smart Robotics

About the Role As a Robot Perception Engineer on the Smart Robotics team at Bright Machines, you will be a hands‑on contributor developing visual inspection solutions for our automation platform. You will work across the full pipeline—from algorithm development to production deployment—helping turn prototype inspection capabilities into reliable, high‑throughput features that operate at scale across our automation lines. In this role, you will develop and optimize computer vision and deep learning models for defect detection, classification, and visual validation. You will collaborate closely with cross‑functional teams, including Mechanical Engineering and Manufacturing Operations, to build end‑to‑end inspection solutions that deliver consistent, accurate results under real‑world factory conditions. What You Will Be Doing Develop computer vision and deep learning algorithms for visual inspection (defect detection, classification, quality validation) and vision‑based navigation (localization, visual servoing, pose estimation) Design data capture strategies, apply augmentation techniques, and train/fine‑tune models for inspection and navigation tasks Build and maintain data pipelines and MLOps workflows for training, evaluation, model versioning, and production monitoring Collaborate with Mechanical engineers to design illumination setups and optimize imaging configurations Support model inference optimization for GPU deployment using CUDA, TensorRT, and related frameworks Harden perception solutions for production reliability and work with field teams on deployment and customer rollouts What You Will Bring BS or MS in Computer Science, Electrical Engineering, Optics, or a related field with 1–3 years in computer vision/ML Strong Python skills with experience in PyTorch or similar frameworks Familiarity with image acquisition, camera systems, and sensor integration Solid understanding of imaging systems (cameras, sensors, optics, lighting) Familiarity with 3D geometry, pose estimation, and basic electronics for vision systems It Would Be Great If You Had Experience with GPU inference optimization and industrial camera standards (e.g., GigE Vision, GenICam) Familiarity with camera sensor characteristics (rolling vs global shutter, dynamic range, noise) Exposure to C/C++, MLOps tools, or data annotation workflows Experience with data annotation, labeling workflows, and active learning strategies Familiarity with robotics/vision topics (SLAM, ROS2, sensor fusion) and manufacturing/quality systems $160,000 - $190,000 a year #J-18808-Ljbffr Bright Machines, Inc.