At Rhoda AI, we’re building the next generation of generalist intelligent robots. We own the full robotics stack from high-performance hardware and robot systems to the infrastructure and state-of-the-art foundation world models that control our robots. Our robots are designed to be generalists capable of operating in complex, real-world environments and handling long-tail edge cases, made possible by our cutting edge research and end-to-end system design. We've raised over $450M and are investing aggressively in model research, infrastructure, hardware development, and manufacturing scale-up to make generalist robotics a reality.

We're looking for research interns — strong PhD students (as well as exceptional Masters/BS students) close to graduation — to work directly with our team on major research and engineering efforts, with the goal of a potential full-time offer at the end of the internship.

What You'll Work On

Your work will be project-specific, scoped to the needs of the major project you're embedded in at the time. Across the team, that spans large-scale video-based robot policy learning, multimodal/VLM architectures, simulation, and robotics-adjacent systems like SLAM and navigation — but your exact focus will be defined by your mentor based on what the project needs.

You'll be contributing directly to a major, ongoing research project rather than working in isolation, and will partner closely with your mentor and the broader research team throughout.

What We're Looking For

• Currently pursuing (or recently completed) a PhD in Computer Science, Robotics, Machine Learning, or a related field — close to graduation preferred; strong Masters/BS candidates with equivalent research experience will also be considered

• Strong foundation in deep learning, with hands-on experience training and debugging large models

• Solid software engineering skills — comfortable writing production-quality research code, not just notebooks

• Experience with one or more of: video/generative models, VLMs or multimodal architectures, robot learning, simulation environments (e.g., MuJoCo, Isaac Sim, Habitat), or SLAM/navigation

• Track record of independent research — publications are a plus but not required, especially for candidates focused on applied/major-project work

• Comfortable working in a fast-moving, resource-constrained startup research environment

The Internship Experience

• Direct collaboration with an assigned mentor from day one, with regular guidance and feedback

• Access to compute resources scoped to your project

• A structured interview process (domain knowledge + coding), a mid-internship check-in, and an end-of-internship evaluation that can lead to a full-time offer

• The opportunity to work on problems that matter to a real generalist-robotics product, not just a standalone research exercise