Remote (US) · ~40–50% travel · Full-timeCompensation: $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
- Salary | $144K–$200K base ($180K–$250K OTE, uncapped variable)
- Equity | Competitive equity
- On-site policy | Remote (US, US daytime hours); ~40–50% travel for on-site deployments
- Visa sponsorship | Not open to any visas (US citizens / Green Card holders only)
- Employment type | Full-time
- Location | Chicago, IL; Indianapolis, IN; Cleveland, OH; Midwest (Remote); NYC/SF/DC hubs