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
Our gloves and wearables are only as good as the data they collect, and that depends on fit, comfort, durability, and how fast someone can put them on. You'll own the physical design of our wearables so they work for hours across many hand sizes, settings, and users, from surgeons to field workers.
What you'll do
- Design and iterate tactile gloves and wearable sensor housings for fit, comfort, and durability
- Integrate sensors, flex circuits, and cabling into soft goods without hurting signal quality
- Make devices fast to put on, take off, clean, and maintain at scale
- Design for many hand sizes and different workflows (e.g. surgical vs. field settings)
- Prototype quickly, run fit and wear testing, and work with suppliers and manufacturers to scale builds
What we're looking for
- 2+ years designing wearables, soft goods, apparel, or consumer hardware
- Strong CAD skills and hands-on prototyping (sewing, patterning, 3D printing, molding)
- Experience integrating electronics into textiles or flexible products
- Experience with gloves, medical wearables, or sports/performance gear is a plus
- Familiarity with materials and manufacturing for soft goods is a plus
Why join
Early, in-person team in San Francisco. You'll own the physical product that every data collector wears.