AI Applications Engineer

The Role

The AI Applications Engineer sits at the intersection of robotics, AI, and hands-on field work. You’re not a pure software engineer and you’re not a pure hardware engineer — you’re the person who can look at a manufacturing challenge, figure out how computer vision or a language model makes the robot smarter, and then actually build and deploy the solution.

You’ll work closely with the sales, software and applications engineering teams to scope AI-enabled solutions, build proofs of concept in our shop, and travel to customer sites to install and commission them. You’ll own your projects end-to-end — from initial design through field deployment and customer training.

This is a builder’s role. Tinkerers and people who get bored at a desk are strongly encouraged to apply.

What You’ll Do

AI Solution Design & POC Development

Work with customers and the sales team to identify where AI — computer vision, object detection, visual language models — creates real leverage in their production process

Design and build proofs of concept that validate the solution before anyone signs anything

Develop documentation, sample code, and integration guides that help customers and internal teams replicate and scale what you’ve built

Field Deployment & Integration

Travel to customer sites to install, configure, and commission AI-enabled robotic cells

Own the full integration: camera placement and calibration, model deployment, I/O configuration, testing, and sign-off

Troubleshoot on-site when things don’t go as planned — you stay until it works

Customer Training & Support

Train customer operators and engineers on the AI capabilities of their Standard Bots deployment

Be a trusted technical resource post-install as customers push the system into new applications

Feed real-world deployment learnings back to our engineering and product teams

Internal Collaboration

Work with the broader applications and engineering teams on new feature testing, peripheral integrations, and platform expansion

Help build the internal knowledge base on AI-enabled applications — what works, what doesn’t, and why

What We’re Looking For

Core Skills (Must have all or most)

Robot programming proficiency or adjacent software experience — if you can write Python without an AI agent, you can probably program a robot having never touched one before

Prior robotics knowledge — anything from high school robotics to professional manipulation experience; we care that you’ve actually worked with robots, not just read about them

Surface-level fluency in ML models and techniques — you can have a real conversation about convolutional neural networks, object detection, and visual language models without Googling the definitions mid-sentence

Technical proficiency in an engineering environment — you write documentation, manage your own projects, work well with a team, and don’t need someone watching over your shoulder

Willingness to travel — up to 50% domestically right now; that number will come down as we grow

Specializations (Must have at least one)

Mechanical Design — pneumatics, camera mounts, end-of-arm tooling for manipulators; bonus points if you’ve designed a gripper

Electrical Design — custom board fabrication, general electrical knowledge for wiring relays and solenoids in automation environments

Machine Vision — you know which cameras and lenses to use for a given application and why; you’ve actually deployed a vision system, not just selected one on paper

Nice to Have

Experience with collaborative robots (UR, Fanuc, KUKA, ABB, or similar)

Hands-on work with vision systems in a production or lab environment (Cognex, Basler, FLIR, or similar)

Familiarity with ROS or other robotics middleware

Background in a manufacturing or industrial automation environment

Experience at a startup — you know what it means to build something from scratch with limited resources