Software Engineer, Data Platform
Preload · San Francisco, CA
AI Summary
Preload is building the data layer for physical AI by capturing how humans interact with the physical world using wearables that record egocentric video, tactile gloves, and EMG signals. This Software Engineer role owns the full stack, from the data collection apps on the devices to the cloud pipelines that store, process, label, and serve large multimodal datasets to robotics and ML teams. It's an early, in-person position in San Francisco as the first dedicated engineer on the data platform.
Job Description
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.
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