Biosignal ML Engineer / Data Scientist

**About Preload** Preload builds the data layer for physical AI. Robots learn mostly from video, but human interaction is much richer: touch, force, and muscle activity. We build a wearable multimodal stack (egocentric video, tactile gloves, EMG) to capture how people actually interact with the physical world, and turn it into datasets robotics teams can train on. We're a YC (F26) team of PhD founders from Johns Hopkins and Caltech with backgrounds at Neuralink, Paradromics, and other neurotech companies. **The role** You'll turn raw, noisy biosignals into features and models that make our data useful for physical AI. **What you'll do** - Build feature extraction pipelines for EMG, tactile, and kinematic signals - Time-align and fuse multimodal streams (video, touch, muscle activity) - Develop models and representations of human manipulation and motor intent - Define data quality metrics and help shape what we collect next - Work closely with sensor and robotics teammates to close the loop from hardware to model **What we're looking for** - 2+ years working with time-series or biosignal data (EMG, EEG, IMU, neural recordings, or similar) - Strong Python and ML fundamentals (PyTorch or similar) - Solid signal processing

skills:

filtering, artifact removal, synchronization - Experience with multimodal or self-supervised learning is a plus - Background in neuroengineering, BME, robotics, or related fields is a plus **Why join** Early, in-person team in San Francisco. You'll own core technical decisions from day one.