Forward Deployed Engineer | Physical AI | Remote (US) | Up to $250K OTE + Equity

"Roads? Where we're going, we don't need roads." We do, however, need engineers. Preferably ones who can land a computer vision model on a factory floor and have it still working when the lights flicker, the cameras fog up, and the forklift driver parks in front of lens three. The company (name withheld, intrigue included) Our client is a physical AI company that has quietly become the platform behind computer vision for some of the biggest names on the planet. Over 1 million developers build on it. Roughly 65% of the Fortune 100 use it, mostly across global manufacturing, logistics, and industrial operations. They have raised north of $99M, including a $77.5M Series B led by one of the most recognisable venture firms in Silicon Valley, with backing from founders whose names you would absolutely recognise if we were allowed to drop them. We are not. Yet. Think of them as the Rebel Alliance of physical AI: small team (about 70 people), enormous impact, and up against the empire of "we've always done it this way" manufacturing. The mission, should you choose to accept it This is not a build-it-and-hope role. Validated proofs of concept already exist. Your job is the critical 0-to-1 phase: taking those POCs into first production deployment inside some of the world's largest factories, warehouses, and construction sites. "Do. Or do not. There is no try." Yoda would have made an excellent Forward Deployed Engineer. You will: • Embed directly with strategic customers (on-site roughly 25 to 50% of the time) and own the journey from working demo to production system • Build and configure data pipelines, edge devices, and computer vision models in messy, real-world physical environments • Wrestle the classic gremlins of real-world CV: lighting variability, camera calibration, model drift, and edge hardware that has opinions • Write production-grade Python, not notebook-grade Python. There is a difference, and the factory floor knows it • Act as the company's eyes and ears in the field, surfacing the gap between what customers say they want and what they actually need, then feeding that straight back to Product and Engineering • Document architectures, write runbooks, and hand off cleanly so customers can run independently "Great Scott!" is the correct reaction when your model that worked flawlessly in staging meets an actual warehouse for the first time. Your job is to make sure the sequel goes better. Who they're looking for Somewhere between 1 and 8 years of experience in a forward deployed, field engineering, solutions architect, or customer-facing software engineering role. They care about competencies, not birthdays. The ideal profile: • Strong Python, plus comfort with systems-level work: Docker, Kubernetes, networking, Linux • You have owned a full technical deployment end-to-end, from first build through customer adoption and post-deployment support • Background in manufacturing, logistics, automotive, robotics, or IoT is gold. Automation, mechanical, or industrial engineers with serious software chops are very welcome • Familiarity with MLOps and CV tooling: model versioning, monitoring, retraining pipelines • You can build trust with a plant executive at 9am and debug a camera feed with a floor operator at 2pm, and enjoy both conversations A word of warning from the careers docket: if your ML experience lives entirely in labs, demos, and notebooks, this is not your droid. They need people who have shipped into physical environments where reality does not read your documentation. The deal • Salary: up to $200K base, with $250K OTE and uncapped variable • Equity: competitive, at a company with genuine traction rather than a pitch deck and a dream • Benefits: full health cover for you and your family, plus generous travel, productivity, and AI tool stipends (yes, really, they pay you to use AI) • Remote-first across the US, with optional city hubs and a relocation bonus if hub life appeals. Travel of 40 to 50% for on-site deployments is part of the gig, so proximity to a major airport matters. Midwest candidates are especially well placed given current customer concentration • Work rights: US citizens and Green Card holders only at this stage; no visa sponsorship available Why this role, why now They are hiring 3 to 5 FDEs this quarter because customer demand has outrun capacity. Large industrial companies simply do not have the internal skills for physical AI, and this team is the one being called in. The stated ambition internally is for this role to carry the same resume weight as a Palantir FDE or a top-tier FAANG stint. Bold? Sure. But so was building a time machine out of a DeLorean. "Never tell me the odds." Fine, we'll tell you anyway: 1M+ developers, most of the Fortune 100, $99M raised, and a product category that is only just getting started. The odds look pretty good. How to apply Send your resume through, or reach out for a confidential chat. Interviews are moving quickly, roughly a four-step process, and the team is decisive. If you have ever looked at a factory floor and thought "this could be so much smarter," this is your invitation. The Force is strong with this one. Marty McFly needed a DeLorean and 1.21 gigawatts to change the future. You just need a laptop, a passport through TSA PreCheck, and production-grade Python. Apply now. Your future self already thanks you.