AI/ML Engineer

Responsibilities

• Design and build core systems intelligence, including recommendation engines and agentic systems
• Train and deploy ML models that form the core of the recommendation engine
• Design evaluations to assess recommendation ability and RL systems to learn from results data
• Build personalization and long-term memory systems into conversational AI
• Use LLMs to enhance the suite of user-facing AI Agents
• Own the end-to-end lifecycle of models, from ideation and training to deployment and monitoring

Requirements

• 4-6 years of experience training and deploying ML models in production
• Proficiency with PyTorch and TensorFlow
• Experience fine-tuning LLMs for agentic systems or complex conversational AI
• Experience with neural network models
• Experience with model deployment and infrastructure (e.g., Docker, Kubernetes, AWS/GCP)
• A desire to build intelligence that drives meaningful human connection

About the Company

Known is a matchmaker that uses general intelligence to empower human connection. Our AI voice agents engage users in deep, multi-modal conversations to help predict human compatibility and create personalized AI companions. We are a team of experienced engineers from companies like Uber Eats, Uber, Faire, and Afterpay, working together in San Francisco.