Software Engineer, Data Platform
$150k to $225k
Against the San Francisco typical range
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.
Description copied from Preload's careers page. Read the full posting before you apply.
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