This job post has expired on July 15, 2026. It is likely that the position has already been filled.
Computer Vision ML Engineer at Mercor
posted 3 months agoComputer Vision ML Engineer | $135/hr | Worldwide Remote
Mercor is seeking a senior Computer Vision ML Engineer for a focused 3–4 week technical assessment engagement, with a strong possibility of extending into a longer build. You will lead a feasibility assessment of a computer vision system designed to identify and grade physical objects from images — delivering findings in a clear, decision-grade report for executive stakeholders.
What You'll Do
- Benchmark baseline model performance on a representative image sample
- Measure accuracy against a held-out evaluation set
- Assess data quality and realistic performance ceiling of the system
- Translate technical findings into an executive-ready feasibility report for a non-technical audience
What We're Looking For
- 5+ years of hands-on experience in computer vision and ML engineering, including fine-tuning modern vision foundation models
- Proven experience classifying or grading physical objects from images (identification, condition scoring, defect detection, or similar)
- Strong evaluation discipline: representative sampling, train/eval separation, honest accuracy benchmarking, and calibration
- Ability to assess production-readiness of a CV system and communicate findings clearly to non-technical stakeholders
Strong Pluses
- Experience with authentication, counterfeit detection, or anomaly detection
- Exposure to private equity diligence or time-boxed advisory engagements
- Familiarity with imaging hardware, capture pipelines (cameras, lighting), and edge or on-prem deployment
This is a fully remote engagement. Compensation is set at $135/hr by Mercor's talent team.
How to apply for this role
- Upload your resume — keep it up-to-date and in English. Mercor will auto-fill your profile from it.
- Complete the AI interview — a 15-minute conversation about your experience. Be ready to discuss specific projects and challenges you've solved.
- Submit your application — only about 20% of applicants finish all the steps, so completing yours puts you well ahead.