We are a pre-seed stage startup funded by top VCs + angel investors, tackling very interesting technical challenges related to personalization with the goal of building a curated internet within the vertical of fashion.

Contact: [email protected]

Who we are: We are the next-gen clothing shopping experience built around a recommendation system that detects nuanced personal style through numerous multimodal variables, as well as conducting sentiment analysis over our chat-bot conversations with our avatar and public-facing personal stylist ARI. ARI returns personalized clothing product recommendations sourced across the entire internet through vector search for users. We currently have an MVP built and are onboarding + collecting feedback from a small subset of our growing waitlist. We are a four person remote team (founder/CEO, Head of Engineering, Head of Design, Head of Partnerships, currently hiring for fifth Head of AI).

Investors: Bloomberg Beta, 1517 VC, Z Fellows, co-founder of Venmo, CEO of Miss Universe, ex-CPO of Hinge, CS faculty @Stanford, AI/ML lead @ Apple, CTO of Linktree, ex-CMO of Bella Hadid’s Kin, @andrewyeung among others.

Founder: Lior Cole dropped out of Cornell CS to build full-time, she is also a worldwide IMG Model. See her TedxCornell talk with a very early ARI chat demo here: https://www.youtube.com/watch?v=gCRcIbdaCDk

Your Role: We're looking for a founding AI engineer who is excited to build products from 0->1, builds fast, pivots easily, and is excited to build a Unicorn with us. You will have the opportunity to own the architecture of our recomendation system. From day one, you'll be an integral part of the team. Our ideal candidate has a strong sense of ownership and enjoys owning projects from inception to scaling in production. If selected, you can expect competitive equity and high autonomy and impact. We are remote and can provide office space in NYC if preferred.

Ideal Candidate: background in early-stage startups, track record quickly shipping high-quality AI-native products at scale, strong ability to creatively approach recommendation system architecture and infra, ability to turn product ideas into engineering solutions, highly motivated