Staff Computer Vision Engineer/Architect

Shanghai, China /
Engineering /
Full Time
Instacart recently acquired Caper AI to help retailers unify the in-store and online shopping experience for customers no matter how they choose to shop. Caper’s cutting-edge, AI-powered shopping carts and automated checkout counters bring together online and offline shopping to create a completely new in-store experience for customers.
 
In addition to acquiring Caper AI’s technology, we’re delighted to welcome the Caper team to the Instacart family. The global Caper team is based primarily in New York City and Shanghai, China, and will bring new hardware expertise to Instacart’s already deep product and technology team. Together, we’re excited to create new ways for retailers to solve for the ever-changing needs of their businesses and customers.
 
About Caper:
Caper builds smart shopping carts powered by deep learning and computer vision to enable a seamless grab-and-go retail experience. We differ from other emerging cashierless technologies because we are the scalable solution. Caper’s autonomous checkout technology is plug and play, meaning it requires no in-store renovation, no operational overhaul, no heavy computations or endless image labeling. Any retailer can buy the carts and their entire store is upgraded with cashierless capabilities. Caper costs less than 1% of other cashierless competitor’s infrastructure. We are already live in-stores and our customers love us!
 
As a part of the Caper team, you’ll be a part of a culture that cares about its people and the future we’re shaping together. At Caper, we may all come from different backgrounds, but we all share one common vision - to fundamentally disrupt the retail industry.

You must have:

    • Have 6+ years of experience in the Computer Vision industry
    • Lead the R&D of robust and large scale computer vision applications before
    • Have strong computer vision knowledge across traditional computer vision to deep learning. Familiar with cutting-edge algorithms commonly used in CV
    • Have strong knowledge of general Machine Learning and Deep Learning including Machine Learning infrastructure, model optimization, model deployment, and serving, data pipelines, and workflows, etc.
    • Be familiar with embedded Computer Vision applications.
    • Be able to track cutting-edge academic work and pick proper ones for implementation.
    • Have strong communication and teamwork skills
    • Be fluent in English at work
    • Be familiar with the Nvidia ecosystem

You are ready to:

    • Architect the overall architecture of various CV projects
    • Lead the research and implementation of the CV applications
    • Review technical designs from the team
    • Lead cutting edge paper exploration and verification