**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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Preload is a company that provides a platform for managing and optimizing data pipelines.