About this role
**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 design and iterate the wearable sensors at the heart of our stack, making them reliable, comfortable, and cheap enough to deploy at scale across very different workflows, from surgery to industrial tasks.
**What you'll do**
- Design, prototype, and iterate tactile, EMG, and other wearable sensors
- Develop analog front-ends, PCBs, and embedded firmware for data capture
- Optimize sensors for specific workflows (e.g. surgical vs. field settings)
- Characterize and validate signal quality, durability, and comfort
- Work with suppliers and manufacturers to move from prototype to scalable builds
**What we're looking for**
- 2+ years designing sensor hardware, wearables, or biosignal acquisition systems
- Experience with PCB design, analog/mixed-signal circuits, and embedded C
- Comfortable going from bench prototype to field-ready device fast
- Experience with EMG, tactile/force sensing, or flexible electronics is a plus
- Background in EE, BME, mechanical, or neuroengineering is a plus
**Why join**
Early, in-person team in San Francisco. You'll own the hardware that everything else is built on.