Eight Sleep
Machine Learning Engineer (Foundation Models & Personalization)
San Francisco · On-site · Full-time · Posted Jan 21, 2026
- Experience
- 2+ years building ML systems in production; consumer-facing product experience is described as ideal.
About the job
Build and ship consumer-facing machine-learning systems for personalized sleep coaching, prediction, and sleep intelligence, from prototyping through production and iteration.
What you'll do
- Develop and deploy models for personalization, prediction, behavior understanding, and actionable interventions.
- Adapt foundation-model capabilities to product workflows and design model evaluation and online experiments.
- Productionize and monitor scalable training and inference pipelines; collaborate across Product, Mobile, Backend, and Clinical.
What they ask for
- 2+ years building ML systems in production.
- Strong ML fundamentals in supervised learning, sequence/time-series modeling, and modern deep learning.
- Hands-on large-scale model training and evaluation with PyTorch/TensorFlow/JAX, plus strong Python engineering practices.
- Experience with personalization systems and data tooling, including SQL, distributed compute, and cloud storage/compute.
Nice to have
- Experience applying LLMs/foundation models to product features.
- Experience with multimodal or health/biometrics data, privacy-preserving approaches, or experimentation/causal inference for personalization.
Tools
PyTorch, TensorFlow, JAX, Python, SQL, Spark, Ray, MCP
AI focus
Apply foundation models, LLMs, multimodal modeling, and policy learning to personalization, coaching, and sleep intelligence; build predictive and behavioral models and related evaluation and production systems.
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