AI Applications Engineer

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 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