AI / ML Engineer
Posted 9 Oct 2025
Advertised as “AI / ML Engineer - Known”
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
- Employment
- On-Site
- Contract
- Full-time
No salary listed for this role.
About the Role
You’ll 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’ll design and ship the systems that make Known feel magical: personalized matching algorithms, adaptive recommendation loops, and natural voice/LLM-based interactions that help users connect meaningfully.
You’ll work closely with the founding team (product, platform, and design) 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 (embedding-based retrieval + LLM re-ranking) 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 (e.g., AI-assisted intake interviews, voice matching, or conversation agents).
-
Deploy and monitor ML models in production with guardrails for performance, fairness, and safety.
-
Run offline & online experiments (A/B and multivariate) to measure real-world outcomes such as engagement, match success rate, and conversation quality.
-
Collaborate cross-functionally with platform engineers and product designers to integrate AI seamlessly into the Known 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.