**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 own the software end to end: from the apps that capture data on our wearables, to the pipelines that store, process, and serve large multimodal datasets.
**What you'll do**
- Build data collection software that syncs video, tactile, and EMG streams from our devices
- Build tools that field teams use to run collection sessions reliably
- Design ingestion pipelines, storage, and metadata/labeling systems in the cloud
- Build APIs and tooling to deliver datasets to ML teams and customers
- Own reliability, monitoring, and scaling as collection grows
**What we're looking for**
- 2+ years as a software engineer building backend or data systems
- Strong Python; experience with cloud infrastructure (AWS/GCP) and data pipelines
- Comfortable working close to hardware: device communication, streaming, timestamps
- Experience with large video or sensor datasets is a plus
- Experience with embedded, mobile, or robotics software is a plus
**Why join**
Early, in-person team in San Francisco. You'll be the first dedicated engineer on our data platform.
Visa sponsorship is offered for this role.
