Description review
Founding Machine Learning Engineer, Computer Vision (Object Detection)
Clera · Remote - New York · back to the listing
HR standards
70/100
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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- Staff AI Engineer - Agent Architecture & Behavior Artisan
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 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.
What You'll Do
• Design and own computer vision architecture for fine-grained identification, adapting foundation vision models to a specific catalog.
• Define accuracy standards by category and build calibrated confidence scores so the product can express uncertainty rather than guess.
• Work with labeling partners to turn model errors into priorities for future data collection.
• Balance expansion into new categories with improving accuracy in existing ones.
• Own the path from model research to production serving, including latency, cost, and reliability.
• Explain the model's capabilities and limitations to technical and non-technical stakeholders.
What We're Looking For
• At least 5 years of applied computer vision experience, including production systems shipped at meaningful scale.
• Industry experience with image or item identification, object recognition, or detection, including fine-grained or instance-level classification where similar items must be distinguished accurately.
• Hands-on production experience fine-tuning and deploying vision transformers or CNNs with PyTorch or TensorFlow.
• Experience adapting foundation vision models, building evaluation frameworks beyond loss metrics, and developing calibrated confidence scoring.
• Experience owning production model serving decisions, including latency, cost, and reliability; familiarity with low-latency APIs is useful.
• Strong communication skills and the ability to lead technical decisions on an open-ended problem.
• Experience with active learning, human-in-the-loop labeling, visual search, marketplaces, or an early-stage startup is a plus.
Compensation & Benefits
Base salary is $200,000 to $260,000 annually. Visa sponsorship is not available.
Location
Hybrid, based in New York, New York, United States.
As 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.
What You'll Do
• Design and own computer vision architecture for fine-grained identification, adapting foundation vision models to a specific catalog.
• Define accuracy standards by category and build calibrated confidence scores so the product can express uncertainty rather than guess.
• Work with labeling partners to turn model errors into priorities for future data collection.
• Balance expansion into new categories with improving accuracy in existing ones.
• Own the path from model research to production serving, including latency, cost, and reliability.
• Explain the model's capabilities and limitations to technical and non-technical stakeholders.
What We're Looking For
• At least 5 years of applied computer vision experience, including production systems shipped at meaningful scale.
• Industry experience with image or item identification, object recognition, or detection, including fine-grained or instance-level classification where similar items must be distinguished accurately.
• Hands-on production experience fine-tuning and deploying vision transformers or CNNs with PyTorch or TensorFlow.
• Experience adapting foundation vision models, building evaluation frameworks beyond loss metrics, and developing calibrated confidence scoring.
• Experience owning production model serving decisions, including latency, cost, and reliability; familiarity with low-latency APIs is useful.
• Strong communication skills and the ability to lead technical decisions on an open-ended problem.
• Experience with active learning, human-in-the-loop labeling, visual search, marketplaces, or an early-stage startup is a plus.
Compensation & Benefits
Base salary is $200,000 to $260,000 annually. Visa sponsorship is not available.
Location
Hybrid, based in New York, New York, United States.