About the Role
Join an early-stage industrial automation startup's engineering team to help develop computer vision systems for factory quality inspection. The system uses first-person cameras to understand manual assembly, recognize process steps, and detect deviations, with the longer-term goal of supporting robotic automation.
What You'll Do
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Build and improve computer vision pipelines for detection, classification, tracking, and temporal understanding.
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Test first-person perception in challenging conditions, including camera motion, occlusion, motion blur, and changing lighting.
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Work with synthetic and real-world data to identify failure cases and improve model performance.
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Train, evaluate, and debug vision models using PyTorch.
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Explore geometric vision, calibration, localization, pose estimation, and 3D perception.
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Optimize models for low-latency inference and edge deployment.
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Build evaluation tools and support deployments to assess performance in real factory environments.
What We're Looking For
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Currently studying computer science, robotics, electrical engineering, mechanical engineering, or a related field.
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Hands-on experience in computer vision, machine learning, or robotics, and comfort working with Python.
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Interest in computer vision and physical AI, with the ability to learn quickly, debug problems, build, and take ownership.
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Experience with PyTorch, OpenCV, object detection, tracking, synthetic data, SLAM or VIO, 3D vision, CUDA or TensorRT, ROS2, or NVIDIA Jetson is helpful.
Compensation & Benefits
Visa sponsorship is available. Relocation from Germany is supported.
Location
On-site in San Francisco, California, United States.
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