Job at a glance
š Description 0-to-1 Deployment: Take validated proof-of-concepts from the pre-sales process and build the first Edge-First Engineering: Deploy and operate computer vision systems on edge hardware in physical Embed with Customers: Work on-site or deeply embedded with the customerās engineering team during Production Engineering: Write production-grade code that will live in the customerās environment.
Be Our Eyes and Ears in the Field: You'll be closer to the customer's real problems than anyone Knowledge Transfer & Handoff: Document your deployment architecture, create runbooks, and train šÆ Requirements Meaningful experience deploying technology in physical-world environments. We value breadth Strong proficiency in Python; experience with systems-level work (Docker, Kubernetes, networking Hands-on experience deploying machine learning or computer vision models to production; you Experience with edge computing hardware and constraints (NVIDIA Jetson, industrial cameras, limited Excellent troubleshooting and debugging skills; youāre the person who figures out why it works in Strong interpersonal skills - you'll be embedded with customer teams and need to build trust š Benefits $4000/yr Travel Stipend to travel anywhere anytime to work alongside other Roboflowers $350/mo Productivity stipend to spend on things that make your work environment more productive $350/mo AI Tools $150/mo Team lunch $500/one time Home office Equity in the company so we are all invested in the future of computer vision