AI Applications Engineer (Boston)
Standard Bots is building the next generation of industrial robots -- hardware that's powerful, affordable, and designed to scale. We're the largest U.S. industrial robotics company by robots shipped, and our robots are showing up on factory floors everywhere from independent machine shops to NASA and Lockheed Martin.
About 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 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.
Responsibilities
- 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
Qualifications
- 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;