AI / ML 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 make finding love one of the defining achievements of abundant general intelligence.

Users join Known by telling us their life story. On average, they spend 27 minutes talking to our conversational AI, sharing the experiences, hopes, and complexities that make them who they are. This gives us an extraordinary depth of personal context, and an even greater responsibility to earn and protect the trust behind it.
We are a team of ex-founders, engineers, and go-to-market operators who've helped build and scaled some of the world's most influential consumer AI products, including Uber, Uber Eats, Airbnb, Bland, and Faire.
We love to work hard, with a high degree of autonomy and ownership. We work together in Cow Hollow, San Francisco.

Learn more

• Known

• Our Launch

• Known’s 10M Seed | TechCrunch

• “You Don’t Need to Swipe Right” - Known | NYT

• Known | FastCompany

• Website

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.

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.

• 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

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