Founding ML Engineer, Computer Vision (Object Detection)

ABOUT THE ROLE Join an early-stage marketplace company as its first machine learning engineer focused on computer vision. You will lead the design and production deployment of fine-grained item identification models, helping users identify products accurately and reliably from photos. WHAT YOU'LL DO - Design computer vision architecture for identifying items by brand, model, edition, and variant, adapting foundation vision models to a specific catalog. - Define category-level accuracy standards and build calibrated confidence scoring so the product can communicate uncertainty appropriately. - Create feedback loops that use model errors to guide labeling priorities in partnership with the labeling team. - Set priorities between expanding category coverage and improving accuracy in existing categories. - Own the model serving path from research through production, balancing latency, cost, and reliability at scale. - Explain model capabilities, limitations, and technical tradeoffs to company stakeholders. WHAT WE'RE LOOKING FOR - At least 5 years of applied computer vision experience, including shipping systems to production at meaningful scale. - Hands-on experience with fine-grained or instance-level recognition, distinguishing visually similar products where near-misses are not acceptable. - Production experience fine-tuning and deploying vision transformers or CNNs using PyTorch or TensorFlow. - Experience adapting foundation vision models to specific use cases, and designing evaluation frameworks that measure progress beyond loss metrics. - Experience with calibrated prediction confidence and ownership of model serving decisions, including latency, cost, and reliability. - Clear written and verbal communication skills, and comfort leading technical direction on an open-ended problem. Active learning, human-in-the-loop labeling, low-latency APIs, and early-stage startup experience are useful. COMPENSATION & BENEFITS Base salary: $200,000 to $260,000 annually. Visa sponsorship is not available. LOCATION Hybrid role based in New York, New York.