Staff Machine Learning Engineer, Tonal

• A proven independent researcher with a strong track record of publications in relevant venues (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, IMWUT/UbiComp, CHI, IEEE TBME, J. Biomechanics, or similar)
• PhD in Computer Science, Electrical Engineering, Biomedical Engineering, Biomechanics, or a related field strongly preferred; we also welcome candidates whose research experience and publication record demonstrate equivalent depth
• Deep expertise in at least one of the following: sensor fusion, biomechanics, physiological signal modeling, or computer vision for human motion
• Hands-on experience designing, training, and debugging transformer architectures, including attention mechanisms, positional encoding for time series, and multimodal tokenization
• Proven ability to train and develop ML models end to end in PyTorch, JAX, or TensorFlow, from data curation through experimentation and analysis
• Strong grounding in signal processing, including filtering, calibration, time alignment, and frequency-domain analysis
• Rigorous experimental design: you know how to build ablations, avoid leakage across subjects, and tell real gains from noise
• Ability to independently define and drive ambiguous research problems toward measurable product impact
• Clear communicator who can explain complex findings to scientists, engineers, and product leaders
• If your experience aligns with what we’re looking for (even if you don’t check every single box), send us your application. We would love to hear from you!

Desirable

• Tonal is looking for a Staff Machine Learning Engineer to join our Sensors & Intelligence team and help build foundation models of human movement and physiology
• You'll work where machine learning, biomechanics, physiology, and computer vision meet
• You'll have access to the largest strength training dataset in the world: millions of workouts captured through cable force and position sensors, cameras, and wearable trackers
• Your job is to turn that multimodal data into general-purpose representations of how people move, exert effort, fatigue, and adapt over time
• Those representations will power the next generation of Tonal's intelligence: adaptive coaching, form feedback, personalized progression, and advanced musculoskeletal health models
• This role combines foundational research with work that reaches our members, and you'll help shape that balance as the team grows
• You'll contribute to defining ML research directions, run rigorous experiments, and publish your work, while partnering with engineering to bring breakthroughs into the product
• Lead research and development of multimodal foundation models that learn from synchronized sensor, video, and physiological signals
• Design self-supervised pretraining strategies for long, heterogeneous time series data
• Develop sensor fusion approaches that handle different sampling rates, sensor noise, synchronization error, and missing modalities
• Advance computer vision methods for 2D and 3D human pose estimation, motion reconstruction, and movement quality assessment
• Build models that estimate biomechanical and physiological quantities such as joint kinematics, load, effort, fatigue, and recovery
• Define evaluation frameworks and benchmarks that measure how well models generalize across users, body types, movements, and equipment conditions
• Validate model outputs against gold-standard references such as motion capture, force plates, and clinical-grade physiological sensors
• Work with ML Engineering to adapt research models for cloud deployment and on-device inference
• Publish regularly at top venues and represent Tonal in the research community through papers, talks, and collaborations
• Mentor scientists and engineers and help set the scientific direction of the Sensors & Intelligence team