Want to know if this job is worth applying to?
Mountain View, California, United States
Onsite
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.
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.
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
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
