At Lightwheel, we are building the simulation infrastructure powering the next generation of Physical AI. Our physics-accurate assets, evaluation tools, and simulation-ready environments help robotics teams move from research to deployment with stronger sim-to-real reliability. As robotics research accelerates globally, our goal is to become the foundational infrastructure layer embedded within leading academic institutions and research labs.

We are seeking a Developer Advocate for the Academic Ecosystem to partner with top robotics labs, PhD researchers, and professors worldwide. In this role, you will integrate Lightwheel infrastructure directly into research workflows. You will collaborate at research depth, support publications and coursework adoption, and represent Lightwheel at conferences such as ICRA, IROS, and CoRL, helping define evaluation standards and research infrastructure for the next generation of Physical AI.

What you will be doing:

• Act as a technical partner to robotics labs, collaborating on architecture, integration, and experimentation using Lightwheel assets, environments, and evaluation tools.
• Integrate Lightwheel infrastructure into active research pipelines, including simulation environments, training workflows, and evaluation systems.
• Contribute to benchmark design and ensure Lightwheel's RoboFinals becomes a credible, widely cited evaluation standard.
• Support and strategically contribute to publications that leverage Lightwheel infrastructure.
• Represent Lightwheel at leading robotics conferences through talks, workshops, tutorials, and challenges.
• Create technical enablement materials such as reference implementations, research guides, tutorials, and experimental templates.
• Track emerging trends in robotics research to identify new academic collaboration opportunities.
• Translate academic feedback into actionable insights for Lightwheel’s product and engineering teams.
• Identify and initiate high-impact academic collaborations with leading robotics institutions.

What we need to see:

• PhD in Robotics, Computer Science, or a related field preferred, or a Master’s degree with significant research experience.
• Hands-on experience with robotics simulation platforms including Isaac Sim and MuJoCo.
• Strong understanding of reinforcement learning, imitation learning, or robot learning workflows.
• Experience designing or contributing to robotics benchmarks and evaluation methodologies.
• Technical writing experience, including peer-reviewed publications or equivalent documentation.
• Ability to present complex technical material to academic audiences.
• Experience collaborating directly with research teams on experimental design and implementation.

Ways to stand out from the crowd:

• Published research in robotics, simulation, or robot learning.
• Experience organizing workshops, challenges, or academic tutorials.
• Familiarity with Isaac Sim, Isaac Lab, OpenUSD, or similar simulation frameworks.
• Experience contributing to open-source robotics projects.
• Background in sim-to-real research or physically grounded asset pipelines.
• Demonstrated success building long-term technical partnerships within academia.