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    Computer Vision & Robotics Intern

    CleraOn-site - San Francisco, California, United StatesPosted 2026-10-29
    This listing's locations
    On-site - San Francisco, California, United States
    Employment
    Full-time
    Workplace
    On site
    Department: Engineering

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    About the Role

    Join an early-stage industrial automation team building computer vision systems to understand manual work in factories. You will work on the core perception system, helping bring real-time quality inspection from controlled experiments into production environments, with potential applications in robotic automation.

    What You'll Do

    • Build and improve vision pipelines for detection, classification, tracking, and temporal understanding.
    • Test first-person perception systems under camera motion, changing viewpoints, occlusion, motion blur, and variable lighting.
    • Use synthetic and real-world data to find failure cases and improve model performance.
    • Train, evaluate, and debug computer vision models using PyTorch.
    • Explore geometric vision, calibration, localization, pose estimation, and 3D perception.
    • Optimize models for low-latency inference and edge deployment.
    • Build evaluation tools and support deployments to learn how systems perform on factory floors.

    What We're Looking For

    • Currently studying computer science, robotics, electrical engineering, mechanical engineering, or a related field.
    • Comfortable programming in Python, with hands-on experience in computer vision, machine learning, or robotics.
    • Hands-on experience with robotics or perception using real sensor or camera data.
    • Curiosity about computer vision and physical AI, plus the ability to learn quickly, build, debug, and take ownership.
    • Experience with PyTorch, OpenCV, object detection, tracking, synthetic data, SLAM/VIO, 3D vision, CUDA/TensorRT, ROS2, or NVIDIA Jetson is a plus.

    Compensation & Benefits

    Visa sponsorship is available. Relocation support from Germany is supported.

    Location

    On-site in San Francisco, California, United States.