Lead multimodal machine learning research at Tonal, using sensor fusion and computer vision to model human movement and physiology remotely from Toronto. The role is remote-first.As a Staff Machine Learning Engineer, you will build foundation models from synchronized sensor, video, and physiological signals. You will shape research directions, run rigorous experiments, and translate findings into adaptive coaching, form feedback, personalized progression, and musculoskeletal health models.

You will also publish and mentor across the Sensors & Intelligence team.Key Responsibilities:

Lead multimodal foundation model research and developmentDesign self-supervised pretraining for heterogeneous time seriesDevelop sensor fusion for noise, alignment,



and missing modalitiesAdvance 2D and 3D human pose estimation methodsAdapt research models for cloud and on-device inferenceRequirements:

Robust publication record as an independent researcherDeep expertise in sensor fusion, biomechanics, physiology, or computer visionHands-on transformer architecture design, training, and debuggingEnd-to-end PyTorch, JAX, or TensorFlow experienceStrong signal processing and rigorous experimental design groundingShape Tonal’s movement intelligence through foundation models, sensor fusion, computer vision, and rigorous machine learning research.

📌 Staff Machine Learning Research Engineer (Winnipeg)
🏢 Tonal
📍 Winnipeg