Own the end-to-end computer vision platform for fine-grained item identification and pricing. Responsibilities include designing and fine-tuning vision models, defining evaluation and confidence standards, building labeling feedback loops, prioritizing coverage versus accuracy, and deploying reliable, low-latency serving infrastructure at scale. The role also communicates model capabilities and trade-offs to technical and non-technical stakeholders.
This is a remote position.
Founding ML Engineer — Computer Vision (Object Detection)
On behalf of an AI commerce tech startup · Remote in North America · Full-time
The build: Our client is an early-stage commerce tech company building production computer vision for precise item identification and pricing. As founding ML engineer, you'll own the identification architecture, data strategy, evaluation standards, and production serving path — end to end, from foundation models fine-tuned toward a specific catalog.
The problem is fine-grained: brand, model, edition, variant. "Close" isn't good enough.
What you'll do
- Design and own the CV architecture for fine-grained item identification — starting from foundation vision models, fine-tuning toward the company's catalog.
- Define what "accurate enough" means per category; build calibrated confidence scoring so the product says "we're not sure" instead of guessing.
- Build the feedback loop between model errors and what gets labeled next, with the labeling lead.
- Decide where to invest: broader category coverage vs. deeper accuracy on today's categories.
- Own the serving path from research to production — latency, cost, reliability at scale.
- Represent the model's capabilities and limits company-wide — including with investors and customers.
Requirements
What we're looking for
- 5+ years applied CV, with at least one system shipped to production at meaningful scale.
- Hands-on fine-grained / instance-level classification — a problem where "close" isn't good enough.
- Fluency in PyTorch or TensorFlow; fine-tuning and deploying vision transformers or CNNs in production.
- Evaluation frameworks for vision models — you know when a model is actually getting better.
- Comfortable being the most senior technical voice on an open-ended problem with no playbook.
- Strong communication — you explain trade-offs to non-technical stakeholders.
Nice to have: resale/marketplace (StockX, GOAT, Vinted, Rebag, The RealReal) or visual search (Pinterest Lens, Google Lens, Syte); active learning / human-in-the-loop pipelines; low-latency API serving at scale; first-ML-hire startup experience.
Similar Jobs
Digital Media • Gaming • Information Technology • Software • Sports • Esports • Big Data Analytics
Engage high-potential and prospective VIP players across communication channels, build relationships, evaluate VIP program eligibility, and optimize player engagement and onboarding strategies. The role supports acquisition efforts for new state launches, gathers customer feedback, and requires adaptability, travel, nights, weekends, and state gaming licensure.
Digital Media • Gaming • Information Technology • Software • Sports • Esports • Big Data Analytics
Manage prediction-market operations, including market creation, configuration, launches, settlement, member support, surveillance, KPI reporting, and liquidity coordination. Monitor activity for anomalies and escalate potential trade-practice violations. Collaborate with engineering, regulatory, analytics, product, clearinghouse, and ecosystem partners to support compliant, reliable market operations and new feature launches. Shift coverage may be required for real-time surveillance.
Digital Media • Gaming • Information Technology • Software • Sports • Esports • Big Data Analytics
Build and manage relationships with high-value players through communications, events, promotions, and issue escalation. The VIP Host will drive revenue, foster loyalty, gather player feedback, monitor market trends, and follow responsible gaming policies. This role requires Spanish fluency, strong customer-facing or account management experience, analytical decision-making, willingness to work nights and weekends, travel flexibility, and the ability to obtain required state gaming licenses.
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
