Computer Vision MLE

About this role

Mercor is placing a senior computer vision engineer on a delivery team for a focused 3-4 week technical assessment engagement, with a strong possibility of extending into a longer build. The work is a feasibility assessment of a computer vision system that identifies and grades physical objects from images. You will benchmark baseline model performance on a representative image sample, measure accuracy against a held-out set, assess data quality and the realistic performance ceiling, and translate the findings into a decision-grade report for a non-technical executive audience. What we are looking for: - 5+ years in computer vision and ML engineering, including hands-on fine-tuning of modern vision foundation models - Experience classifying or grading physical objects from images (identification, condition or quality scoring, defect detection, or similar) - Strong evaluation discipline: representative sampling, train/eval separation, honest accuracy benchmarking, and calibration - Ability to assess the feasibility and production-readiness of a computer vision system and communicate the verdict clearly to a non-technical audience Strong pluses: - Experience with authentication, counterfeit, or anomaly detection - Exposure to private equity diligence or other time-boxed advisory work - Familiarity with imaging hardware and capture pipelines (cameras, lighting) and edge or on-prem deployment Engagement is remote. Compensation set by Mercor's talent team.

Skills & domains

• ai-training
• rlhf
• sme
• annotation
• Data Analysis