You will own the matchmaking and recommendation systems for a voice-first AI dating app where 80% of introductions lead to real-world dates. As an early engineer, you'll transition these core algorithms from zero to production scale, working alongside a founding team with deep experience from Uber, Cash App, and Faire.
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AI/ML Engineer at Known
Are you tired of building internal tools or ad-tech? Join a $10M seed-stage consumer AI startup backed by Forerunner and NFX that is completely redesigning modern dating. As an early AI/ML Engineer, you will own the core matching engine for a voice-first platform where users spend 27 minutes per day interacting with the AI. We are looking for engineers who helped scale recommendation systems at companies like Instagram or Tinder and want to do it again from the ground up. This is a rare chance to work on a product where your models are the entire user experience, offering a $250k-$400k base plus significant equity in San Francisco.
About this role
Role overview
About the company
Known
Known is a matchmaker that talks to users and supports them like a friend. Our mission is to empower humanity by applying general intelligence to human connection.
Users join Known by telling us their life story. On average, our new users talk to our AI voice agent for 27 minutes, giving us a uniquely intimate multi-modal data set.
We are a team of engineers who’ve created some of the most widely used AI-driven consumer products including Uber Eats, Uber, Faire and Afterpay.
We love to work hard, with a high degree of autonomy and ownership. We work together in Cow Hollow, San Francisco.
How It Works: On Known, who you see is intentional by design.
There's no feed to scroll. No feeling that someone better is one profile away. It starts with a conversation with Known. Understanding who you are, how you live, and what you're actually looking for. You're introduced to one person at a time, guided by what Known learns about you. Your profile is created for you, dynamically. It evolves as Known gets to know you better. When you're curious about someone, you can ask Known questions. The things you'd normally wonder but never quite know. When interest is mutual, Known takes care of what's next. Schedules are coordinated. The venue is chosen. And the date is set. Less scrolling. More
What you'll do
What you will do
- Design and implement the primary matchmaking and ranking algorithms that power the 1-to-1 daily introduction experience.
- Scale experimental recommendation systems into high-availability production environments to support a rapidly growing user base.
- Lead and grow a small technical team, establishing the engineering culture for the ML and personalization org.
Who you are
Who this is a fit for
- Proven experience building and scaling user-facing recommendation or ranking systems at a consumer-growth company like Tinder, Instagram, or Spotify.
- Early-stage veteran who joined during a 0→1 phase and stayed long enough to see their systems scale in production.
- Direct track record of creating models that impact user-facing product surfaces rather than internal tools, fraud, or ad-tech.
Why this role
Why this role is remarkable
- High-impact ownership of the core product value where your models directly drive user connection without swiping or endless feeds.
- Exceptional pedigree and backing from top-tier firms like Forerunner, NFX, and Pear VC in a $10M seed round.
- Strong early traction with users spending 27 minutes on average talking to the AI, creating a rich signal for matchmaking.
Jack & Jill
How Jack & Jill work together
I get to know what you’re great at, then find roles you’d never find yourself.Ok, I'll go first. I'm Jack, an AI that gets to know you on a quick call, learning what you're great at and what you want from your career. Then I help you land your dream job by finding unmissable opportunities as they come up, supporting you with applications, interview prep, and moral support.
I recruit from Jack’s network and make the intro when I spot a great match.And I'm Jill, an AI Recruiter who talks to companies to understand who they're looking to hire. Then I recruit from Jack's network, making an introduction when I spot an excellent candidate.
Meet Jack
Jack gets to know what you're great at and what you want next, then searches 15 million jobs daily and helps you discover roles at companies like this.
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Tell Jack what you want
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