Forward Deployed Engineer
Roboflow · USA
About this role
## Forward Deployed Engineer (FDE) — Roboflow ### Who We Are Roboflow’s mission is to make the world programmable. We build tools, community, and resources to help people build and deploy computer vision workflows powered by AI. Today, over 1M+ developers use Roboflow’s open source and hosted tools across industries like healthcare, construction, logistics, and more. ### What You’ll Do As a **Forward Deployed Engineer**, you’ll be the first technical hands-on person for new customer Roboflow deployments. After Sales and Solutions Architecture validate the technical approach, you’ll take the project from **proof-of-concept to production**—the critical **0-to-1** phase where vision meets reality. You’ll **embed with customers** (typically **4–12 weeks per engagement**) to: - Build and deploy their first production computer vision workflows on Roboflow - Handle real-world constraints (unfamiliar infrastructure, unreliable connectivity, edge hardware limits) - Write production-grade code that runs in the customer’s environment - Act as **Roboflow’s eyes and ears** in the field—feeding insights back to Product and Engineering - Create documentation and runbooks, then hand off to Implementation Engineers for scaling ### Role & Responsibilities - **0-to-1 Deployment:** Turn validated PoCs into first production deployments (data pipelines, model optimization, edge configuration, customer integration) - **Edge-First Engineering:** Deploy and operate CV systems on edge hardware in physical environments - **Embed with Customers:** Build trust, transfer knowledge, and establish foundations for long-term success - **Production Engineering:** Manage real-world issues like lighting variability, calibration, model drift, latency, and hardware constraints - **Be Our Eyes and Ears:** Surface gaps between what customers think they want vs. what they actually need - **Knowledge Transfer & Handoff:** Document architecture, create runbooks, train teams, and enable smooth scaling - **De-risk New Deployments:** Identify and resolve technical risks early - **Shape the Deployment Playbook:** Codify repeatable patterns, templates, and reusable artifacts ### The Skillset You’ll Bring - Experience deploying technology in **physical-world environments** (factories, warehouses, construction sites, labs, etc.) - Strong **Python** proficiency; systems-level experience (Docker, Kubernetes, networking, Linux) is highly valued - Hands-on experience deploying **ML/CV models to production** (understanding the gap from notebook to pipeline) - Edge computing experience and constraints (e.g., **NVIDIA Jetson**, industrial cameras, limited connectivity, on-prem security) - Excellent troubleshooting/debugging (works in staging, fails in production—find why) - Strong interpersonal skills for embedded customer work across executives, engineers, and operators - Experience in one or more target verticals: **manufacturing, logistics, food processing, automotive, retail** - Willingness to travel **~40–50%** for on-site deployments **Preferred Attributes** - Professional services / deployment engineering / forward deployed engineering experience - Familiarity with CV/MLOps practices (model versioning, monitoring, retraining) - Deep industrial subject matter expertise (throughput, defect rates, inspection points) - Background in IoT, embedded systems, or infrastructure engineering - “Tinkerer” mindset (hands-on curiosity with hardware, networking, and home projects) ### Where You
Listing freshness
CronJobs last confirmed this listing 1h ago. If its source stops confirming the opening for seven days, this page is removed from active inventory.