{"id":1809249,"url":"https://alion.io/job/clera-founding-ml-engineer-computer-vision-object-detection","title":"Founding ML Engineer, Computer Vision (Object Detection)","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":30,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":6,"computed_at":"2026-10-05T05:45:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","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":{"min":200000,"max":260000,"currency":"USD","period":"year","gross":null,"usd_annual":260000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Computer Vision","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Machine Learning","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-10-03T20:02:07Z","employer_posted_date":"2026-10-03","last_verified_at":"2026-10-05T23:25:28Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"About the Role\nAs the founding machine learning engineer at an early-stage internet marketplace company, you will set the technical direction for visual item identification. You will build production models that distinguish between closely related items and provide reliable predictions that support customer decisions.\nWhat You'll Do\nDesign computer vision architecture for fine-grained item identification, starting with foundation vision models and adapting them to the marketplace catalog.\n\nSet category-specific accuracy standards and build calibrated confidence scoring so the product can communicate uncertainty.\n\nDevelop feedback loops that use model errors to prioritize future labeling in collaboration with the labeling team.\n\nGuide tradeoffs between expanding category coverage and improving accuracy in existing categories.\n\nOwn the path from model development to production serving, balancing latency, cost, and reliability.\n\nExplain model capabilities and limitations to technical and non-technical stakeholders.\n\nWhat We're Looking For\nAt least 5 years of applied computer vision experience, including shipping a system to production at meaningful scale.\n\nHands-on experience with fine-grained or instance-level classification, where distinguishing similar items matters.\n\nStrong fluency in PyTorch or TensorFlow and practical experience fine-tuning and deploying vision transformers or CNNs.\n\nExperience designing and running vision model evaluations that measure improvement beyond loss metrics.\n\nExperience owning model serving decisions, including latency, cost, reliability, and calibrated confidence scoring.\n\nComfort taking technical ownership of an open-ended problem and communicating tradeoffs clearly.\n\nExperience with active learning, human-in-the-loop labeling, low-latency model APIs, or an early-stage startup is a plus.\n\nCompensation & Benefits\nAnnual base salary: $200,000 to $260,000.\nLocation\nOn-site in San Francisco, California, United 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