Why This Role Stands Out
This internship offers an incredible opportunity to develop cutting-edge computer vision and robotics skills within an innovative industrial automation startup. You'll gain hands-on experience building and optimizing complex vision pipelines, making you an ideal candidate if you are eager to learn and contribute to real-world AI solutions. Apply now to be part of this exciting journey in shaping the future of factory automation!
Quick Overview
Job Description
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
Build and improve computer vision pipelines for detection, classification, tracking, and temporal understanding.
Test first-person perception in challenging conditions, including camera motion, occlusion, motion blur, and changing lighting.
Work with synthetic and real-world data to identify failure cases and improve model performance.
Train, evaluate, and debug 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 assess performance in real factory environments.
What We're Looking For
Currently studying computer science, robotics, electrical engineering, mechanical engineering, or a related field.
Hands-on experience in computer vision, machine learning, or robotics, and comfort working with Python.
Interest in computer vision and physical AI, with the ability to learn quickly, debug problems, build, and take ownership.
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.