ML Research Scientist (Health & Sensing)

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Company Overview

A leading global sleep fitness technology company is focused on improving human performance through better sleep. The organization combines advanced hardware, software, artificial intelligence, machine learning, and health technology to create personalized, data-driven sleep and recovery experiences.

Its technology uses temperature regulation, physiological sensing, and intelligent software to help individuals improve sleep quality, recovery, and overall health. The organization serves customers internationally and works with high-performing individuals, athletes, and health-conscious consumers.

The organization operates as a high-performance technology team focused on rapid innovation, rigorous execution, and continuous improvement. Its research and development efforts bring together multidisciplinary teams to develop products at the intersection of sleep science, machine learning, sensing technology, and personalized health.

The Role

The organization is seeking an ML Research Scientist (Health & Sensing) with a passion for applying artificial intelligence and machine learning to sensor data and health-related problems. The role will focus on transforming physiological and environmental data into personalized, intelligent health and fitness experiences.

The successful candidate will work closely with cross-functional R&D and production teams to research, prototype, validate, and deploy machine learning solutions. The role provides an opportunity to develop new health metrics and intelligent systems that can support better sleep, improved recovery, and healthier behaviors.

The position will involve working with data including heart rate, heart rate variability, sleep metrics, wearable sensor information, and other physiological signals. The successful candidate will approach complex problems systematically and use data-driven methods to develop impactful products and experiences.

Key Responsibilities

• Advance adaptive thermoregulation systems that continuously learn and respond to micro-events such as restlessness and awakenings.
• Design machine learning policies that optimize comfort and sleep quality in real time using reinforcement learning and closed-loop control.
• Develop multimodal health foundation models that integrate physiological signals with environmental and contextual information.
• Leverage large-scale sleep datasets, wearable sensor data, and other sources of physiological information to develop meaningful health insights.
• Build high-fidelity physiological simulations that model how daily behaviors can influence sleep and next-day readiness.
• Research and develop non-invasive, continuous models of healthy aging using biosignals and physiological data.
• Transform sensor data into personalized health and fitness experiences.
• Collaborate with R&D, engineering, and production teams to prototype and deploy research-driven solutions.
• Apply machine learning research to real-world health and sleep challenges.
• Analyze large datasets to identify meaningful patterns, insights, and opportunities for new health metrics.
• Contribute to the development of innovative AI-powered technologies designed to improve health outcomes.

Required Qualifications

• Expertise in at least one area of machine learning or artificial intelligence, such as self-supervised learning, multimodal machine learning, model optimization, natural language processing, or large language models.
• Strong interest in applying machine learning to health-related problems and datasets.
• Experience using a programming language such as Python, C, or C++ to manipulate data, extract insights from large datasets, and train machine learning models.
• 3+ years of practical experience applying machine learning to real-world problems, or relevant quantitative and qualitative research and analytics experience.
• PhD in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, or a related quantitative field with a strong publication record; or a Bachelor’s or Master’s degree with publications at leading research venues.
• Research or publication experience at recognized conferences such as NeurIPS, ICML, ICLR, AAAI, CVPR, ICCV, ACL, EMNLP, INTERSPEECH, or comparable venues.
• Strong analytical, problem-solving, and research skills.
• Ability to work effectively with multidisciplinary teams and translate research concepts into practical products.

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