Robotics ML Intern — VLA & Diffusion Policy
Company: Nimo Technology, Inc. Location: Mountain View, CA (Onsite) Employment Type: Internship (Full-time or Part-time) Compensation: $35–$50/hr (DOE)
About Nimo
Nimo Technology is building the next generation of intelligent robots powered by foundation models. We’re a small, fast-moving team in Mountain View working at the intersection of large-scale robot learning and real-world deployment.
About the Role
We’re looking for a Robotics ML Intern to work alongside our engineering team on Vision-Language-Action (VLA) models and diffusion-based policies. This is a hands-on role — you’ll get to train real models, run experiments on real robots, and ship code that matters. Great fit for a CS or Robotics Master’s student who wants serious research + production experience before graduating.
What You’ll Do
- Assist in training and fine-tuning VLA models (e.g., OpenVLA, π0) and diffusion policies
- Help build and clean datasets from teleoperation and demonstration collection
- Run training experiments, log results, and contribute to ablation studies
- Support deployment of trained policies onto real robot hardware
- Read recent papers and prototype new ideas with the team
Required Qualifications
- Currently pursuing an MS (or final-year BS) in Computer Science, Mechanical Engineering, Robotics, EE, or related field
- Solid PyTorch skills and comfort with deep learning fundamentals
- Coursework or project experience in computer vision, imitation learning, or reinforcement learning
- Familiar with at least one of: VLA models, diffusion policies, behavior cloning, or transformer-based architectures
- Strong Python; comfortable working in a Linux environment
- Self-driven, curious, and willing to learn fast
Nice to Have
- Personal or course projects involving robot learning, manipulation, or LLMs/VLMs
- Experience with ROS/ROS2 or any real robot hardware
- Familiarity with simulation environments (Isaac Sim, MuJoCo, LIBERO, CALVIN)
- GitHub contributions to lerobot, OpenVLA, or similar open-source projects
- Prior internship or research lab experience
Why Join Us
- Work directly on frontier robot learning problems with real hardware
- Mentorship from engineers actively training and deploying VLA models
- Small team, high ownership — your work has real impact, not just busywork
- Potential to convert to a full-time role after graduation
How to Apply
Submit your resume + a short note (2–3 sentences) on a robot learning, ML, or VLA-related project you’ve worked on. Links to GitHub, papers, or demo videos encouraged.
