Forward Deployed Engineer

Job Description

Job Description

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 versioning, monitoring, and retraining pipelines.

Why Join

• Join a company with genuine traction: a platform already used at massive scale by household-name enterprises.
• Strong, uncapped OTE plus equity and a generous benefits package, including full health coverage and travel, productivity, and AI-tools stipends.
• Remote-first across the US with optional hubs and a relocation bonus, plus a flexible, async-friendly culture.
• A career-defining field role where you own real production outcomes for major customers.

Details

• Location: Remote (US); Midwest strongly preferred (Chicago, Indianapolis, Cleveland); NYC/SF/DC hubs
• Work policy: Remote with ~40–50% travel for on-site customer deployments
• Compensation: $144K–$200K base ($180K–$250K OTE) + equity
• Visa sponsorship: Not available — US work authorization required (US citizen / Green Card)
• Employment type: Full-time