Founding Wearables Engineer
Myto
Founding Wearables Engineer
Myto
Digitizes frontline knowledge into actionable SOPs
We’re building AI that learns from the factory environment and turns that knowledge into better decisions on the floor. The point is simple: better decisions and better execution while the work is happening.
Our Palo Alto-based team brings experience from Stanford, BCG, Porter, and Mercedes-Benz. Our founders have built a unicorn and raised hundreds of millions from firms like Sequoia and Tiger Global. This is a chance to join a well-funded early-stage company already working with active design partners and a long waitlist of manufacturers eager to work with us.
We believe this is one of the largest unsolved opportunities in AI: building systems that help run the physical world. If you want to build AI that leaves the browser and changes how the physical world operates, you should talk to us.
We are looking for a founding wearables engineer to lead our camera-first wearable capture effort: smart glasses, head-mounted cameras, body-worn devices, rugged mobile hardware, or whatever gets the job done. This is a hands-on senior IC role for someone who can move fast, evaluate existing hardware, customize where needed, and get working systems into the field. AR is not the priority right now. Reliable procedure capture and hands-free troubleshooting are.
Full-time. Local or hybrid preferred for hardware iteration and field testing, but we care more about finding the right person quickly than enforcing a strict location requirement.
The anticipated base salary range for this position is $100,000–$300,000 annually. Actual compensation will depend on a variety of factors, including experience, skills, qualifications, and expected impact. In addition to base salary, this role includes a meaningful equity component. The salary range listed reflects Myto's good-faith estimate of the compensation range for this position at the time of posting.
Myto provides a SaaS platform that captures frontline factory knowledge to reduce production downtime. It ingests data like SOPs, maintenance logs, tickets, and machine history, and uses wearable AI glasses to record operators’ troubleshooting and shift handoffs, turning tacit know-how into structured SOPs, workflows, and training content. The system builds AI agents that autonomously assist with troubleshooting, generate documentation, and coordinate handoffs, surfacing likely root causes and past fixes when equipment issues arise. Unlike others, Myto emphasizes converting tribal knowledge into a growing, shareable knowledge base with fast deployment and minimal IT requirements, linking machine history with operator expertise to improve diagnostic speed and prevent repeat failures. The goal is to shorten downtime, boost production efficiency, and preserve critical know-how as experienced workers retire.
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