Staff Machine Learning Engineer, Sensors & Intelligence
Core
Lead research and development of multimodal foundation models for understanding human movement, performance, and physiology using synchronized sensor, video, and physiological data.
Role type
Staff Machine Learning Engineer (Research & Product)
Builds
General-purpose representations of human movement, exertion, fatigue, and adaptation for intelligent coaching and health applications
Domain
Biomechanics, Physiological Signal Processing, Computer Vision, Sensor Fusion
Deliverable
production ML models
Required skills
Transformer architectures, PyTorch/JAX/TensorFlow, sensor fusion, biomechanics, physiological signal modeling, computer vision, time-series analysis, experimental design, model evaluation
Preferred skills
Foundation model pretraining, musculoskeletal modeling tools (OpenSim, MuJoCo), wearable physiological signals (IMU, PPG, HRV, EMG), model compression, human-subject research
Technologies
PyTorch, JAX, TensorFlow, OpenSim, MuJoCo, MyoSim
Responsibilities
Design self-supervised pretraining for heterogeneous time-series datasets; Develop sensor fusion techniques for multi-modal data; Advance computer vision for human pose estimation and motion reconstruction; Build models to estimate biomechanical and physiological measures; Establish evaluation frameworks and benchmarks; Validate predictions against clinical-grade reference measurements; Partner with engineering for cloud and on-device deployment; Publish research at leading venues; Mentor scientists and engineers
Seniority
Staff, independent research lead & mentorship
