Forward Deployed Engineer

**Remote (US) · \~40–50% travel · Full\-time** **Compensation:** $144K–$200K base ($180K–$250K OTE) \+ equity ### **About the Company** Our client is a well\-funded, growth\-stage computer vision / physical\-AI company whose platform is used by more than a million developers and a large share of the Fortune 100, primarily across manufacturing and industrial settings. They help the world's largest companies take vision models from proof\-of\-concept to real production on the factory floor. Founded 2019 · \~70 people · Industry: AI, Software Development, Devtools ### **The Role** You'll take computer vision deployments from proof\-of\-concept to production at major manufacturing, logistics, and industrial organizations. This is a hands\-on, 0\-to\-1 builder role for someone who thrives in ambiguous, real\-world environments — embedding directly with customer teams and shipping production\-grade systems that hold up outside the lab. **What you'll be doing** * Embed with customers on\-site (roughly a quarter to half your time) to take validated POCs to first production deployment. * Build and configure data pipelines, edge devices, and vision models in real physical environments like factories, warehouses, and construction sites. * Act as the field's voice back to Product and Engineering — surfacing the gap between what customers ask for and what they actually need. * Write production\-grade Python and handle the messy realities of real\-world CV: lighting, camera calibration, model drift, and edge hardware limits. * Document deployment architectures, write runbooks, and hand off cleanly once customers are running independently. **Tech stack:** Python, Docker, Kubernetes, Linux, NVIDIA Jetson, computer vision, ML/MLOps, edge computing, industrial cameras ### **Requirements** * Roughly 1–8 years in a forward\-deployed, field, solutions\-architect, or customer\-facing software engineering role. A junior path (1–3 years) works with strong FAANG\-tier internships plus time at a leading FDE company, high\-growth startup, or in a customer\-facing SWE role. * Direct ownership of a customer\-facing technical deployment end to end — from initial build through customer adoption and post\-launch support. * Strong Python plus real systems\-level experience (Docker, Kubernetes, networking, Linux). * Automation, mechanical, or industrial engineers with strong software engineering skills are welcome. * A BS in computer science, engineering, or a related technical field. * Highly motivated, coachable, and low\-ego — eager to learn, open to feedback, and a genuine team player. * Able to communicate and build trust with everyone from executives to engineers to floor operators. * Willing to travel 40–50% for on\-site deployments; a Midwest base (Chicago / Indianapolis area) is strongly preferred. ### **Nice to Haves** * Background in manufacturing, logistics, automotive, or robotics/automation. * Familiarity with MLOps and CV tooling — model versionin