AI Developer Technology Intern, Robotics - 2027

Roboticsconnected; Santa Clara (CA); On-site; USD 34,000 - 55,000; Part time

Job summary

NVIDIA’s DevTech team is seeking a passionate intern to work on robotics foundation model training and inference, powering intelligent robotic systems on NVIDIA platforms. You will develop training pipelines, optimize inference performance, and apply modern DL/ML techniques to real-world robotics challenges.

Ideal candidates are pursuing a Master’s or PhD in CS/Robotics/AI, with strong Python, C/C++, and CUDA skills, plus experience in PyTorch and transformer architectures.

Qualifications

• Pursuing a Master’s or PhD in Computer Science, Robotics, AI/ML, Electrical Engineering, or related field.
• Strong programming skills in Python; familiarity with C/C++ and CUDA a plus.
• Experience with deep learning frameworks (PyTorch).
• Understanding of transformer architectures and large-scale model training.
• Basic knowledge of robotics concepts (kinematics, control, perception, or simulation).
• Curious, self-motivated, and excited about solving open-ended challenges at NVIDIA.

Responsibilities

• Develop and optimize training pipelines for robotics foundation models on NVIDIA GPU clusters.
• Profile, analyze, and optimize model inference performance on NVIDIA platforms.
• Apply modern DL/ML techniques to real-world robotics problems.
• Collaborate with NVIDIA teams to influence design of architectures, software platforms, and programming models.
• Build samples, reference implementations, and documentation to educate developers on NVIDIA robotics AI technologies.
• Discuss approach and results with senior DevTech engineers.

Skills

Python

C/C++

CUDA

PyTorch

Transformer architectures

Robotics concepts

Education

Master’s or PhD in CS/Robotics/AI/ML

Tools

DeepSpeed

Megatron-LM

FSDP

NeMo

CUDA toolkit

Job description

Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. We are theDevTech teamserving the robotics ecosystem in China. As NVIDIA DevTechs, we are defined asexperts in application optimization on NVIDIA platforms— through code optimization, new application architectures, and cutting-edge DL/ML algorithms. Our mission spans performance analysis & modeling, applying modern DL/ML techniques to real-world problems, deep-diving on GPU architecture, building samples/libraries/SDKs, and collaborating with architecture, software engineering, and product management to improve NVIDIA’s current and future platforms. We are looking for a passionate intern to work onRobotics Foundation Model training and inference— powering the next generation of intelligent robotic systems on NVIDIA’s platform.

What You’ll Be Doing:

• Develop and optimize training pipelines for robotics foundation models (e.g., vision-language-action models, world models) on NVIDIA GPU clusters

• Profile, analyze, and optimize model inference performance on NVIDIA platforms

• Apply modern DL/ML techniques to real-world robotics problems

• Collaborate closely with NVIDIA architecture, research, libraries, tools, and system software teams to influence the design of next-generation architectures, software platforms, and programming models

• Build samples, reference implementations, and documentation to educate developers on NVIDIA robotics AI technologies

• Discuss your approach and results together with senior DevTech engineers

What We Need to See:

• Currently pursuing a Master’s or PhD degree in Computer Science, Robotics, AI/ML, Electrical Engineering, or a related technical field

• Strong programming skills inPython; familiarity withC/C++andCUDAis a plus

• Experience with deep learning frameworks (PyTorch,)

• Understanding of transformer architectures and large-scale model training

• Basic knowledge of robotics concepts (kinematics, control, perception, or simulation)

• Curious, self-motivated, and excited about solving open-ended challenges at NVIDIA

Ways to Stand Out from the Crowd:

• Experience with distributed training (DeepSpeed, Megatron-LM, FSDP, NeMo)

• Experience with inference optimization (SGlang, vLLM)

• Familiarity with NVIDIA robotics platforms (Isaac Sim, Isaac Lab, GR00T)

• Publications or project experience in embodied AI or robotics foundation models

• Ambitious to grow and learn about building ML applications, optimization, and software engineering