{"id":3762545,"url":"https://alion.io/job/clera-founding-machine-learning-engineer-computer-vision-object-detection","title":"Founding Machine Learning 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":39,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":6,"computed_at":"2026-11-09T06:03:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["New York, 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":true,"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":"PyTorch","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-11-04T17:22:29Z","employer_posted_date":"2026-11-04","last_verified_at":"2026-11-09T19:42:01Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"About the Role\nAs the founding computer vision engineer at an early-stage internet marketplace, you will set the technical direction for identifying and valuing items from images. You will build production models that distinguish closely related items and communicate uncertainty clearly, helping users make decisions with confidence.\nWhat You'll Do\nDesign and own computer vision architecture for fine-grained identification, adapting foundation vision models to a specific catalog.\n\nDefine accuracy standards by category and build calibrated confidence scores so the product can express uncertainty rather than guess.\n\nWork with labeling partners to turn model errors into priorities for future data collection.\n\nBalance expansion into new categories with improving accuracy in existing ones.\n\nOwn the path from model research to production serving, including latency, cost, and reliability.\n\nExplain the model's 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 production systems shipped at meaningful scale.\n\nIndustry experience with image or item identification, object recognition, or detection, including fine-grained or instance-level classification where similar items must be distinguished accurately.\n\nHands-on production experience fine-tuning and deploying vision transformers or CNNs with PyTorch or TensorFlow.\n\nExperience adapting foundation vision models, building evaluation frameworks beyond loss metrics, and developing calibrated confidence scoring.\n\nExperience owning production model serving decisions, including latency, cost, and reliability; familiarity with low-latency APIs is useful.\n\nStrong communication skills and the ability to lead technical decisions on an open-ended problem.\n\nExperience with active learning, human-in-the-loop labeling, visual search, marketplaces, or an early-stage startup is a plus.\n\nCompensation & Benefits\nBase salary is $200,000 to $260,000 annually. 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