{"id":3834353,"url":"https://alion.io/job/clera-computer-vision-robotics-intern-4","title":"Computer Vision & Robotics Intern","company":{"id":2706,"name":"Clera","domain":"getclera.com","url":"https://alion.io/company/clera","size_band":"11-50","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":80,"open_postings":39,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":6,"computed_at":"2026-11-08T05:47:12Z"}},"role":"Early Careers","role_family":"Early Careers","seniority":"intern","employment_type":"internship","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":true,"relocation_package":true,"has_equity":false,"technologies":[{"name":"Computer Vision","optional":false},{"name":"CUDA","optional":false},{"name":"Localization","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenCV","optional":false},{"name":"Physical AI","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"ROS","optional":false},{"name":"SLAM","optional":false},{"name":"Synthetic Data","optional":false},{"name":"TensorRT","optional":false}],"status":"live","first_seen_at":"2026-11-05T17:25:14Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-08T08:26:38Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"About the Role\nJoin an early-stage industrial automation team building computer vision systems to understand and verify manual assembly work. You will work closely with the technical leadership on perception systems that can detect process deviations in real factory environments.\nWhat You'll Do\nBuild and improve vision pipelines for detection, classification, tracking, and temporal understanding.\n\nTest first-person perception in the presence of camera motion, changing viewpoints, occlusion, motion blur, and variable lighting.\n\nUse synthetic and real-world data to find failure cases and improve model performance.\n\nTrain, evaluate, and debug PyTorch vision models.\n\nExplore geometric vision, calibration, localization, pose estimation, and 3D perception.\n\nOptimize models for low-latency inference and edge deployment.\n\nBuild evaluation tools and experiments to measure performance in real-world conditions.\n\nSupport factory deployments and assess system performance on the shop floor.\n\nWhat We're Looking For\nCurrently studying computer science, robotics, electrical engineering, mechanical engineering, or a related 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