Known - Founding Machine Learning Engineer- San Francisco, CA (In-Person)
- 200k-375k Cash + Equity
About the RoleWe'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 doIt'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 InvestorsWe're backed by Eurie Kim and Kirsten Green at Forerunner Ventures (the investors behind Decagon, Faire, and Oura), NFX and PearVC.
