NIO→
AI Robotics Simulation Intern at NIO in San Jose-
InternshipOn-siteSan Jose-$79k–$96k/yr
Skills
c++ programmingpython programming3d geometry processingmesh generationsurface reconstructionrendering apisgpu programmingdebuggingrobotics simulatorscollision detection algorithmscontact modelingcuda programmingparallel computingtensor-native operationspython bindings for c++sim-to-real transfersystem-level thinking
Job Description
Summary: NIO is a pioneer in the premium smart electric vehicle market, focused on advancing technologies in autonomous driving and robotics. The AI Robotics Simulation Intern will work on enhancing high-fidelity simulation infrastructure for robotic manipulation, contributing to various projects including physics-driven simulations and contact dynamics analysis.
Responsibilities:
- Massively parallel GPU simulation architecture and scalable infrastructure for robot learning
- Advanced contact mechanics and numerical methods for contact-rich robotics
- System Identification (System ID) and practical sim-to-real transfer techniques
- Industry-scale research execution for embodied foundation models
- Production-quality, well-documented simulation tools, wrappers, or mesh processing modules integrated into our codebase
- A comprehensive technical report documenting:
- Experimental design (e.g., for System ID or stress-testing)
- Evaluation methodology for contact stability and the sim-to-real gap
- Quantitative benchmarking results
- An internal presentation to the robotics team demonstrating the new tools during live policy rollouts
Required Qualifications:
- PhD or strong MS student in Computer Science, Robotics, Computer Graphics, or related field
- Strong C++ and Python programming skills
- Solid foundation in 3D geometry processing, mesh generation, or surface reconstruction
- Experience with rendering APIs (OpenGL/WebGL/Vulkan) and GPU programming
- Strong debugging skills and system-level thinking
Preferred Qualifications:
- Hands-on experience with robotics simulators (MuJoCo, Isaac, Bullet, etc.)
- Knowledge of collision detection algorithms (e.g., GJK, EPA) and contact modeling (LCP, soft contacts)
- Experience with CUDA, parallel computing, or tensor-native operations (e.g., PyTorch)
- Familiarity with writing Python bindings for C++ code (e.g., pybind11) and integrating them into ML pipelines
- Prior experience working with real robot hardware or sim-to-real transfer pipelines
Required Skills: C++ programming, Python programming, 3D geometry processing, Mesh generation, Surface reconstruction, Rendering APIs, GPU programming, Debugging, Robotics simulators, Collision detection algorithms, Contact modeling, CUDA programming, Parallel computing, Tensor-native operations, Python bindings for C++, Sim-to-real transfer, System-level thinking