Early Career Radar
ML & AI · Not specified

Computer Vision & Robotics Intern

Clera

Location
San Francisco, CA
Opening date
Opened today
Work authorization
F-1/CPT/OPT acceptedCompensation & Benefits Visa sponsorship is available.
Source
2027 Tech Jobs
Employer posting

Job description

Captured from employer · Oct 29, 2026

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.

Private to you

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