SHIFT Studios
Machine Learning / Computer Vision Engineer
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Company Description
SHIFT Studios is an e-Commerce growth studio focused on creating world-class online shopping experiences that scale. With over 50 years of combined experience, the team blends strategy, design, technology, and performance to build commercially focused solutions for ambitious brands. As a certified Shopify Premier Partner, SHIFT Studios designs, develops, and optimises high-performing e-Commerce websites across Shopify and Shopify Plus, from conversion-driven UX to complex back-end integrations. The in-house team collaborates across the entire e-Commerce ecosystem, working with leading platforms in loyalty, reviews, subscriptions, ERPs, and advanced integrations to deliver scalable, stable, and future-ready builds. SHIFT Studios partners with growth-minded founders and teams across fashion, tech, food, luxury, and more, united by a commitment to craft, performance, and measurable results.
Alongside our client work, we build and scale our own ventures. This role sits with Cubby - an AI-powered household food agent that turns a video of your fridge into a fully managed pantry, expiry alerts, recipes, and a weekly shop, all with one tap to approve. Cubby is at an early, fast-moving stage. You'll be employed by SHIFT Studios and dedicated to building Cubby's core technology from the ground up.
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Role Description
This is the most important early engineering hire for Cubby. The entire product rests on one thing working: turning a short video of a fridge or a photo of a receipt into clean, structured, trustworthy inventory. You'll own that end to end, working directly with Cubby's CTO and founding team.
You'll build and own:
- The computer-vision pipeline that identifies food items from video and images at consumer-grade cost and speed
- Receipt and e-receipt OCR, line-item parsing, and product mapping
- The inference layer feeding Cubby's Pantry and Expiry agents - storage inference, category priors, shelf-life prediction, and confidence scoring
- The evaluation harness and data feedback loops that make the models sharper as usage grows
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You'll move fast, ship to real users, and shape the technical direction of a category-defining product from day one.
Qualifications
- Demonstrated experience shipping production computer vision or applied ML in a consumer or high-throughput setting.
- Comfort across the full stack of ML delivery: model selection, fine-tuning, inference optimization, and the engineering that puts it in front of real users.
- Rigorous thinking about cost, latency, and confidence - not just accuracy in a notebook.
- Experience with vision-language models and structured extraction is a strong plus.
- Food, retail, grocery, or logistics domain experience is a bonus, not a requirement.
- Ability to stand up early data infrastructure when the sprint needs it.
- Appetite for 0→1 ownership in an ambiguous, fast-moving venture environment.
- Bachelor's degree in Computer Science, Machine Learning, or a related field, or equivalent professional experience.
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