Description review
Founding ML Engineer, Computer Vision (Object Detection)
Clera · Remote - New York · back to the listing
HR standards
71/100
solid
Title ↔ description
92/100
strong
Reads as
Machine Learning Engineer
100% confident
What this role officially is
data scientist — ESCO, the EU occupation classification
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist
How others title the same work
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Startups
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What the listing never says
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
The listing, marked up
Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.
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.
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.