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Sr. AI & Automation Engineer, Robotics

Intuitive
Sunnyvale, USA
Full-time
Senior · 30+ years experience
Onsite
Discovered 3 days ago
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Full Job Posting

Qualifications

  • What You Bring We care more about real depth in a few of these areas than shallow coverage of all of them. • Hands-on work with real robots. You've built testing, automation, or evaluation systems that ran on real robot hardware or other physical systems via software interfaces, not only in the cloud or in simulation. • AI and automation you've built and put into daily use. You've built LLM-agent workflows, AI tool integrations, copilots, or automation pipelines for real engineering work and mea
  • You write production-quality Python, can read C++, and are comfortable with Linux, CI/CD, Docker, containerized services, APIs, and distributed systems.
  • Strong candidates often come from robotics, autonomous systems, physical AI, or robot- learning research, and have applied AI tooling to real hardware. You're comfortable working across disciplines in a fast-moving research environment and can explain trade-offs clearly to researchers and engineers alike.
  • If you don't check every box, we still want to hear from you.
  • Education • BS, MS, or PhD in Computer Science, Robotics, Electrical Engineering, Mechanical Engineering, or a related technical field. • Advanced degree (MS or PhD) preferred. Bonus Points None of these are required. They're signals, not gates, and any one of them is a nice plus. • Robotics simulation, such as NVIDIA Isaac Sim/Lab or MuJoCo • Evaluating AI/ML, robotics, or robot-learning systems • Surgical or medical robotics, including da Vinci Research Kit (dVRK) systems • ROS 2 or other robo

Responsibilities

  • Build and integrate AI tools, APIs, and agent workflows that automate engineering and research work across the team.
  • Automate the training and fine-tuning workflow, from setting up experiments to launching, tracking, and comparing runs, so researchers can reproduce results without hand-built scripts.
  • Build automation and integration workflows that help researchers and engineers evaluate new ideas in simulation and on real robots, quickly, reliably, and at scale.
  • Design evaluations and experiments that show, with statistical confidence, whether a change is a real improvement.
  • Build logging, analysis, and debugging tools that help the team understand results and failures, and that turn robot sessions into data the team can train on.
  • Make what you build reliable, secure, and safe to run, with human approval where it matters and responsible use of AI throughout.
  • Evaluate emerging AI tools, models, and technologies, and bring in the ones that deliver measurable impact.
  • Measure the impact of what you build, document it clearly, and make successful tools part of how the team operates.

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