Machine Learning Engineer (Foundation Models & Personalization)
Core
Build and ship consumer-facing AI systems for personalization, coaching, and sleep intelligence using foundation models and data-driven insights.
Role type
Senior Machine Learning Engineer (Foundation Models & Personalization)
Builds
Personalized sleep experiences, readiness forecasting, event detection, and individualized recommendations via the Eight Sleep Pod.
Domain
Consumer Health & Wellness / Sleep Technology / AI
Deliverable
production ML models
Required skills
End-to-end ML system ownership, supervised learning, sequence/time-series modeling, modern deep learning, large-scale model training/evaluation, personalization systems (ranking/recommendations, lifecycle modeling), Python engineering, SQL, distributed compute (Spark/Ray), cloud storage/compute.
Preferred skills
LLM/foundation model application (tool use, RAG, structured outputs), multimodal data (sensor signals + context), health/biometrics data, privacy-preserving approaches (federated learning, differential privacy), experimentation frameworks/causal inference.
Technologies
PyTorch, TensorFlow, JAX, Spark, Ray, SQL, LLMs, RAG
Responsibilities
Build and deploy ML models for personalization and prediction; adapt foundation models to product workflows; develop user behavior models connecting longitudinal signals to interventions; design evaluation strategies and run online experiments; productionize models with scalable pipelines and monitoring; collaborate with cross-functional partners to ship features.
Seniority
Senior, hands-on IC