Staff Machine Learning Engineer, Sensors & Intelligence
Core
Building foundation models of human movement and physiology using multimodal sensor, video, and physiological data to power adaptive coaching and health models.
Role type
Staff Machine Learning Engineer (Research & Product)
Builds
General-purpose representations of human movement, exertion, fatigue, and adaptation; adaptive coaching and musculoskeletal health models.
Domain
Fitness technology, biomechanics, and sensor intelligence.
Deliverable
production ML models
Required skills
Multimodal foundation model development, self-supervised pretraining for time series, sensor fusion, computer vision for human pose estimation, biomechanical/physiological quantity estimation, evaluation framework design, PyTorch/JAX/TensorFlow, signal processing, experimental design, model deployment.
Preferred skills
Distributed training/scaling, musculoskeletal modeling tools (OpenSim, MuJoCo), wearable physiological signals (IMU, PPG, HRV, EMG), personalization/few-shot adaptation, model compression, human subjects research.
Technologies
PyTorch, JAX, TensorFlow, OpenSim, MuJoCo, MyoSim.
Responsibilities
Lead R&D of multimodal foundation models; design self-supervised pretraining strategies; develop sensor fusion approaches; advance computer vision methods for motion reconstruction; build models for biomechanical/physiological estimation; define evaluation frameworks; validate outputs against gold-standard references; adapt research models for cloud/on-device deployment; publish research; mentor team members.
Seniority
Staff, independent researcher with strategic direction and mentorship.
