Field Engineer, Surgical Data Collection
$100k to $150k
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 run our surgical data collection: working with surgeons and clinical partners to capture expert surgical skill with our sensor stack.
What you'll do
- Plan and run data collection sessions with surgeons and clinical partners
- Set up, calibrate, and troubleshoot sensors in surgical and simulation environments
- Ensure data quality, protocol compliance, and proper documentation
- Coordinate with partner sites on scheduling, approvals, and logistics
- Feed field insights back to hardware and software teams
What we're looking for
- 1+ years in a clinical, surgical, medical device, or clinical research setting
- Comfortable in ORs or surgical training environments
- Hands-on with technical equipment and troubleshooting on the fly
- Familiarity with IRB processes and research protocols is a plus
- Background in BME, clinical engineering, or as a surgical tech or clinical specialist is a plus
Why join
Early, in-person team in San Francisco, with travel to partner sites. You'll build our surgical data program from the ground up.
Description copied from Preload's careers page. Read the full posting before you apply.
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