A sleep fitness company designing technology to improve nightly recovery and long-term health.
ML Research Scientist (Health & Sensing)
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You'll join a small, focused research team building models that interpret biological signals—temperature, heart rate, respiration, movement—to quantify sleep quality and drive real-time health interventions. The work spans raw sensor data through production inference: designing experiments, prototyping architectures in PyTorch, and collaborating with hardware and software engineers to ship algorithms onto devices in millions of homes. We're after someone who treats a restless night as a fascinating signal-processing puzzle and wants their research to measurably improve how people feel every morning.
What they're looking for
- 3–10 years of hands-on machine learning experience, with a strong track record in time-series, physiological sensing, or related health domains.
- Fluent in Python and modern ML frameworks (PyTorch, TensorFlow, or JAX) plus the numerical stack—NumPy, Pandas, Scikit-learn.
- Comfortable working end-to-end: from exploratory data analysis on messy real-world sensor streams through deploying models in resource-constrained production environments.
- Deep understanding of signal processing fundamentals and experience with at least one relevant modality—PPG, ECG, EEG, accelerometry, or thermal sensing.
- Clear communication and a collaborative instinct; you'll partner closely with hardware, firmware, and product teams rather than throwing models over a fence.