Machine Learning Engineer (Foundation Models & Personalization)

Join the Sleep Fitness Movement At Eight Sleep, we’re on a mission to fuel human potential through optimal sleep. As the world’s first sleep fitness company, we’re redefining what it means to be well-rested and building the most advanced hardware, software, and AI technology to make it possible. Our products power peak mental, physical, and emotional performance by transforming every night of sleep into a personalized, data-driven recovery experience. We are trusted by high performers, professional athletes, and health-conscious consumers in over 30 countries worldwide. Recognized as one of Fast Company's Most Innovative Companies in 2019, 2022, and 2023, and twice named to TIME's “Best Inventions of the Year.” We operate like a high-performance team: fast, focused, and motivated by impact. We don’t just ship; we iterate, refine, and obsess over the details that help our members sleep better and wake up stronger. Every role at Eight Sleep is a chance to create cutting-edge technology, collaborate with world-class talent, and help shape a future where sleep isn’t passive - it’s a powerful tool for living better. If you’re tired of the ordinary and driven to build at the edge of what’s possible, this is your moment. Join us and lead the movement that’s transforming how the world sleeps and what we’re all capable of when we wake up. High Standards. No Apologies We operate wit [... source excerpt omitted ...] urable improvements for members. This role is ideal for someone who loves end-to-end ownership: from problem framing → prototyping → offline evaluation → online experimentation → production deployment → iteration. How you’ll contribute Build and deploy ML models that improve sleep experiences through personalization, prediction, and behavior understanding (e.g., readiness forecasting, event detection, individualized recommendations). Apply and adapt foundation-model capabilities to real product workflows (LLM + tools/RAG, multimodal modeling, policy learning), including MCP-style integrations where helpful. Develop user behavior models that connect longitudinal signals (sleep, [... source excerpt omitted ...] rement. Design evaluation strategies (offline metrics, slice-based analysis, calibration, reliability, fairness) and partner with Product to run high-quality online experiments. Productionize models: scalable training/inference pipelines, model monitoring, drift detection, alerting, and continuous improvement loops. Collaborate with cross-functional partners (Product, Mobile, Backend, Clinical) to scope requirements and ship high-impact features. What you need to succeed Minimum Qualifications 2+ years building ML systems in production, ideally for consumer-facing products. Strong ML fundamentals across supervised learning, sequence/time-series modeling, and modern deep lear