AI Applications Engineer (Glen Cove, NY)
Indexed description
Note: This role requires up to 50% domestic travel. That number goes down as we grow the team, but right now you're in the field -- a lot. If that's not for you, this probably isn't the right fit.
Also note: If you're looking for a role where you train models and push code, this isn't it. This is a mechanical + electrical + software trifecta that happens to use AI as a tool. The factory floor is your office.
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
- 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
- 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
- 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
- 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
- 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
- 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
Compensation Range: $120K - $150K
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