Mashgin builds self-checkout kiosks that use A.I. to scan multiple items without barcodes, reducing checkout time by 10x. We’re completely recreating the checkout experience in an industry that’s seen little innovation in decades. We are live in over 1,500 locations across the world and processing 5m+ transactions monthly. We are growing fast.
We were part of YC W15 and closed a $62.5 million series-B funding round in May 2022 at a $1.5B valuation.
At Mashgin, we are developing the future of checkout experiences. We aim to reduce the friction between customer desires and their ability to be on their way.
Our ecosystem is anchored by the only 3D computer vision and deep learning based checkout system in the world. With customers across a wide spectrum of verticals including the NFL, MLB, and Aramark, our company and product adoption are growing at a rapid pace.
We value autonomy of ones work, a culture of respect for one another, and building products with empathy for our customers.
You will be our first Designer who will work on introducing the experience of computer vision based checkout to the masses in a physical retail environment
Whether it be convenience stores, sports arenas, cafeterias, or airport micro markets, our product allows users to experience fast checkout without needing to scan barcodes. Just set it down, pay, and you're on your way. You will own the User Interface for all Mashgin products including customer facing products, client tools, and internal tools. This will span all mediums as well including mobile, applications, tablet, and our core product. If you have a strong visual design sense and a passion for taking ownership of all user interfaces then this role is for you!
We're looking for someone who can be based in the Bay Area (our HQ is in Palo Alto) or someone who is based in South America to work with our engineering team.
You Will Be
What We Offer
Mashgin is proud to be an equal opportunity employer. Individuals seeking employment at Mashgin are considered without regards to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation.
Our system reconstructs the entire scene in 3D in real-time using multiple cameras and uses deep learning to separate, identify and count items.
3D Computer Vision, Convolutional Neural Nets, C++, Python, Node.js.