openashbyhqgv
Forward Deployed Engineer
Roboflow
LocationNY, SF or Remote (US)
WorkplaceRemote
EmploymentFullTime
Posted2026-05-18T18:02:25.383+00:00
Last observed2026-06-13 05:23:23.037819
Job idgv-roboflow:ashbyhq:444ee288-cb72-4751-b16d-67c27749e901
WHO WE ARE Our mission is to make the world programmable. Sight is one of the key ways we understand the world, and soon this will be true for the software we use, too. We’re building the tools, community, and resources needed to make the world programmable with artificial intelligence. Roboflow simplifies building and using computer vision models. Today, over 1M+ developers, including those from half the Fortune 100, use Roboflow’s computer vision AI open source and hosted tools. That includes counting cells to accelerate cancer research, improving construction site safety, digitizing floor plans, preserving coral reef populations, guiding drone flight, and much more. Roboflow is supported by great customers and investors, having raised over 63 million from Y Combinator, Google Ventures, Craft Ventures, Sam Altman, Lachy Groom, amongst other leading software investors. Roboflowers are passionate builders who value ownership, accountability, and a bias toward action. We’re curious, hands-on with new tech, and prefer showing our work over talking about it. Many of us have a founder mindset and thrive in our high-autonomy environment. WHAT YOU’LL DO We’re hiring Forward Deployed Engineers (FDEs) to be the first technical hands on our new customer’s Roboflow deployments. After our Sales and Solutions Architecture team closes a deal and validates the technical approach, you step in to take it from proof-of-concept to production, the critical 0-to-1 phase where vision meets reality. You’ll embed directly with new Customers, working alongside their engineering and operations teams to build and deploy their first production computer vision workflows on Roboflow. This is the most difficult, important and rewarding phase of the customer journey. Infrastructure is unfamiliar, data pipelines need to be built, edge devices need to be configured, and models need to perform in real-world conditions, not just in a demo or a lab. The FDE role is more than just execution, you are also our eyes and ears in the field. You'll see the gap between what a Customer thinks they want, and what they actually need. That insight is invaluable, and you'll feed it directly back to our Product and Engineering teams, shaping the Roboflow platform and solution offerings. The best FDEs don't just deploy solutions; they surface the problems worth solving next. Once you’ve proven the deployment works in production and the customer’s team is equipped to operate it, you hand off to our Implementation Engineers who scale, optimize, and expand the solution across additional use cases. You’re the tip of the spear, the person who makes the first deployment work, no matter what it takes; the adventurer, the explorer, the builder. Five years from now, FDE at Roboflow on a resume should mean what a few years at Palantir or a FAANG company means. That's the bar we're hiring against. ROLE AND RESPONSIBILITIES - 0-to-1 Deployment: Take validated proof-of-concepts from the pre-sales process and build the first production deployment. This includes data pipeline setup, model optimization, edge device configuration, and integration with customer infrastructure. - Edge-First Engineering: Deploy and operate computer vision systems on edge hardware in physical environments. Where conditions are unpredictable and connectivity is unreliable. This is hands-on, hardware-heavy work. - Embed with Customers: Work on-site or deeply embedded with the customer’s engineering team during the initial deployment phase (typically 4–12 weeks per engagement). Build trust, transfer knowledge, and establish the foundation for long-term success. - Production Engineering: Write production-grade code that will live in the customer’s environment. Handle the messy realities of real-world computer vision: lighting variability, camera calibration, model drift, network latency, and edge hardware constraints. - Be Our Eyes and Ears in the Field: You'll be closer to the customer's real problems than anyone els
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