---
title: 'AI / ML Engineer at Known'
canonical: 'https://feeny.ai/job/ai-ml-engineer-known-san-francisco-msw4s80gaaq1'
type: 'job'
last_seen: '2026-09-09'
---

# AI / ML Engineer at Known

- **Company:** Known
- **Location:** San Francisco, CA
- **Compensation:** $200k–$375k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-04-24
- **Last confirmed live:** 2026-09-09
- **Apply:** https://jobs.ashbyhq.com/known/b1961855-7af2-4465-97c2-2a95a52b3d40

## Job description

## KNOWN - FOUNDING MACHINE LEARNING ENGINEER

- San Francisco, CA (In-Person)
- 200k-375k Cash + Equity

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.

Learn more

- Known https://apps.apple.com/us/app/known-swipeless-dating/id6748926392
- Our Launch https://x.com/Celesteamadon/status/2018023250408960293?s=20
- Known’s 10M Seed | TechCrunch https://techcrunch.com/2025/12/19/known-uses-voice-ai-to-help-you-go-on-more-in-person-dates/
- “You Don’t Need to Swipe Right” - Known | NYT https://www.nytimes.com/2025/11/03/technology/ai-dating-apps.html
- Known | FastCompany https://www.fastcompany.com/91484596/every-dating-app-has-ai-now-can-it-help-make-better-matches
- Website https://www.knowndating.com/

## ABOUT THE ROLE

We’re looking for founding machine learning engineers to continue to design and build Known’s core systems intelligence, driving our recommendation engine and agentic systems.

This is a unique opportunity to work with an ultra-personal data-set, combining voice transcripts, images, and structured user data to create both personalized AI companions as well as predict human compatibility. You’ll work directly with Chen Peng, former head of ML at Uber Eats and Faire.

## WHAT YOU’LL DO

It’s up to you to decide what part of the ML stack you’re most excited about working on.

This could be:

- Training and deploying ML models that form the core of our recommendation engine
- Designing evals to assess recommendation ability and RL systems to learn from results data
- Building personalization and long-term memory systems into Known’s conversational AI
- Using LLMs to enhance our suite of user facing AI Agents

You will own the end-to-end lifecycle of your models, from ideation and training to deployment and monitoring.

## REQUIREMENTS

- 4-6 years experience training and deploying ML models in production, leveraging PyTorch and TensorFlow
- Applying or fine-tuning LLMs to build agentic systems or complex conversational AI
- Experience with neural network models
- Experience with model deployment and basic infrastructure (e.g., Docker, Kubernetes, AWS/GCP)
- You want to build intelligence that could lead to a million marriages and babies

## OUR INVESTORS

We’re backed by Eurie Kim and Kirsten Green at Forerunner Ventures (the investors behind Decagon, Faire, and Oura), NFX and PearVC.

## About Known

## Company Overview
- **One-liner**: Known is building a personalized voice‑AI matchmaker that talks to users, understands their preferences, and supports them like a friend.
- **Entity Type**: Private (Seed stage – raised $9.7M)
- **Headquarters**: San Francisco, California, USA
- **Founded**: Not publicly available
- **Founders**: Not publicly available

## Core Business
- Primary industry: Artificial intelligence / Consumer matchmaking
- Target customers: B2C (individuals seeking meaningful human connections)
- Mission: “Empower humanity by applying personalized general intelligence to human connection.”

## Products & Services
- **Personalized Voice‑AI System**: A conversational agent that ingests speech‑to‑text and sentiment data, uses an in‑house LLM to model compatibility, and powers agentic chat with real‑world integrations (reservations, Uber, calendar). Delivered as a SaaS mobile/web experience.

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: Total funding $9.7M (raised as of latest round)
- **Notable Investors/Partners**: Not publicly disclosed in available sources
- **Growth Signals**: Small, highly focused team of engineers who previously shipped major consumer AI products at Uber Eats, Uber, Faire, and Afterpay; recent funding indicates strong investor confidence.

## Competitive Advantages
- **Personalized general intelligence**: The system learns each user’s compatibility preferences and adapts its conversations and suggestions over time.
- **Real‑world integrations**: Directly books reservations, rides, and calendar events – going beyond typical chatbots.
- **Tiny, high‑caliber team**: Engineers from some of the most‑used AI consumer products of the last decade, enabling rapid iteration and deep domain expertise.

## Strategic Focus
- Current priority is to build the “one AI product they’ve always wanted to work on” – a deeply personal, voice‑first assistant for human connection. Near‑term focus likely includes growing the user base, refining the LLM for compatibility, and expanding integration partners.

## Why Work Here
- **Culture**: Small, tight‑knit engineering team with a “build what you love” ethos. The company values shipping high‑impact AI consumer experiences.
- **Work policy**: Hybrid – flexible on‑site presence in San Francisco (typical time on‑site: flexible).
- **Notable perks**:
  - Top‑tier health, vision & dental insurance
  - Yearly company offsites
  - Lunch and dinner provided on‑site
  - Unlimited drinks & snacks
  - Office dog (Dolly)
- **Engineering environment**: Opportunity to work across the full stack (STT, LLM, agentic chat, cloud infrastructure) and shape a product from early stage.

## Sources
1. [known.com/careers](https://known.com/careers)

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- [Product Engineer, React](https://feeny.ai/job/product-engineer-react-known-san-francisco-depch0k94bd3) — San Francisco, CA
- [Founding Growth](https://feeny.ai/job/founding-growth-known-san-francisco-w8w58afxmgnn) — San Francisco, CA
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