Overview
ABOUT THE ROLE
Full job description
ABOUT THE ROLE As the founding machine learning engineer, you will set the technical direction for fine-grained visual item identification at an internet marketplace platform. You will build production models that identify specific brands, models, editions, and variants, helping users make informed decisions with confidence. WHAT YOU'LL DO
- Design and own computer vision architecture, adapting foundation vision models to specialized catalog identification.
- Define category-level accuracy standards and develop calibrated confidence scoring so the product can communicate uncertainty.
- Build feedback loops that use model errors to guide labeling priorities in partnership with the labeling team.
- Balance broader category coverage against deeper accuracy in existing categories.
- Own the path from model research to production serving, including latency, cost, and reliability.
- Explain model capabilities and tradeoffs to technical and non-technical stakeholders. WHAT WE'RE LOOKING FOR
- At least 5 years of applied computer vision experience, including production systems delivered at meaningful scale.
- Hands-on experience with fine-grained or instance-level recognition, distinguishing between visually similar items where near-misses are not sufficient.
- Production experience fine-tuning and deploying vision transformers or CNNs with PyTorch or TensorFlow.
- Experience adapting foundation vision models to specific use cases or catalogs.
- Ability to design and run evaluation frameworks that measure model improvements beyond training loss.
- Experience with calibrated confidence scoring and ownership of model serving decisions, including latency, cost, and reliability.
- Strong written and verbal communication, and comfort providing technical leadership on an open-ended problem. COMPENSATION & BENEFITS Base salary: $200,000 to $260,000 annually. Visa sponsorship is not available. LOCATION Hybrid role based in New York, New York.
Tips for this job
Practical JobOpportunity guidance. These tips do not replace official rules or create new eligibility requirements.
- Tailor the CV and application to the responsibilities and required skills stated on the official employer page.
- Use concrete evidence of relevant work, projects and measurable results rather than generic claims.
- Confirm location, work authorization, remote restrictions and sponsorship terms before applying.
- Apply through the original employer or official recruitment destination shown on this page.
JobOpportunity.info helps you discover and organize source listings. Confirm eligibility, dates, salary/funding and application instructions on the original source before submitting anything.
Apply through JobOpportunity →