AI / ML Engineer - Known
Remote • San Francisco • FullTime
Posted 1y ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
AI Engineer
About the job
You will be the technical founder driving the machine learning and AI backbone behind Known, an intelligent, compatibility-driven dating platform that blends psychology, data, and human-like conversation. You will design and ship the systems that make Known feel magical, including personalized matching algorithms, adaptive recommendation loops, and natural voice/LLM-based interactions to help users connect meaningfully. You will work closely with the founding team to shape both the data and ML foundations and the user-facing experiences that differentiate Known. This is a hands-on role with ownership across research, prototyping, and production deployment.
Responsibilities
- Design and implement multi-stage matching systems for compatibility scoring, search, and personalization.
- Develop and maintain ML pipelines for data ingestion, feature generation, model training, evaluation, and inference.
- Prototype and productionize agentic workflows for natural-language and voice interactions.
- Deploy and monitor ML models in production with guardrails for performance, fairness, and safety.
- Run offline & online experiments to measure real-world outcomes.
- Collaborate cross-functionally to integrate AI seamlessly into the user experience.
Requirements
- 3+ years in applied ML or data science engineering roles, ideally working on recommendation, search, or personalization systems.
- Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, JAX, Hugging Face).
- Experience with LLMs, embeddings, and agentic workflows.
- Understanding of A/B testing and human-in-the-loop system design for model evaluation in production.
- Familiarity with ANN search systems and modern MLOps tools is a plus.
- Reinforcement learning or preference modeling experience is a strong plus.
- Commitment to building safe, fair, and human-centered AI experiences.