📅 Mar 23
Own the end-to-end development and production deployment of visual inspection solutions, building and optimizing computer vision and deep learning models for reliable, high-throughput defect detection on factory automation lines.
Founding ML Engineer, Computer Vision (Object Detection)
🕒 3 days ago
Computer VisionFine-grained RecognitionInstance-level RecognitionVision Transformers
📜 Description
- Set category-level accuracy standards and develop calibrated confidence scoring.
- Use model errors to guide labeling priorities with the labeling team.
- Balance broader category coverage with deeper accuracy in existing categories.
- Take models from research to production serving, owning latency, cost, and reliability.
- Explain model capabilities and tradeoffs to technical and non-technical stakeholders.
🛠️ Requirements
- 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.
✨ Benefits
- Base salary: $200,000 to $260,000 annually. Visa sponsorship is not available.
- Design and own computer vision architecture for specialized catalog identification.
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.
Similar jobs
Search more Computer Vision Engineer jobs
📅 Oct 7, 2025
Develop and optimize computer vision and machine learning models for deployed robots, using large-scale sensor data to improve environmental awareness and inventory insights.
📅 Sep 30, 2025
Own and advance production computer vision pipelines for automated video masking, improving segmentation, tracking, accuracy, speed, and scalability while translating product needs into deployed ML solutions.
📅 Sep 17, 2025
As a Senior Computer Vision Engineer, you will design and implement advanced computer vision algorithms, collaborate with teams, and mentor junior engineers while optimizing solutions for real-world applications.
📅 Aug 24
As a Principal Computer Vision Engineer, you'll architect and optimize computer vision pipelines, blending classic techniques with deep learning to enhance retail analytics.