PhD Intern, AI/ML in Wireless L1/L2

NVIDIA's work is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing with the invention of the GPU, which has proven effective at solving complex computer science problems. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms for AI, robotics, and self-driving cars. We are looking to grow our company with the smartest people in the world, and there has never been a more exciting time to join NVIDIA.

NVIDIA Aerial CUDA Accelerated RAN (ACAR) is a framework for building high-performance, software-defined, cloud-native Radio Access Network functions over NVIDIA CPU/GPU/DPU based systems, driving our AI native 6G solutions.

About the Role

We are seeking a self-motivated Intern to drive the adoption of AI/ML functions in the Physical (Phy) and Medium Access Control (Mac) layers of our Aerial Software. This position offers the opportunity to work on cutting-edge technology, using NVIDIA's world-class compute platforms to advance the field of AI native wireless stacks to achieve the Spectral and Energy efficiency goals of 6G.

Responsibilities

As a member of the Aerial RAN team working on AI Native stacks, you will be contributing to:

• Develop and optimize AI/ML modules for functional blocks specifically in wireless signal processing.
• Perform literature survey to understand the prior art on AI/ML for RAN.
• Analyze and identify suitable ML architectures for the RAN functions of interest.
• Collaborate with multi-functional teams to optimize the Over-The-Air (OTA) performance and compute complexity with DevTech and other business units within NVIDIA.
• Benchmarking of OTA performance improvements with AI models and compute needs on different platforms.
• Iteratively train, test & modify model architectures for performance improvements.

Requirements

• Full-time PhD student doing research in the fields of AI and Wireless domains.
• Ability to work as an Intern for at least 6 months or more, starting from the last week of January 2026.
• Thorough understanding of wireless Layer1/Layer2 functions and algorithm aspects.
• Excellent grip on AI and ML concepts, techniques, and abreast of the latest developments in this field.
• Deep understanding of Transformers, CNNs, and other ML Architectures and their use cases.
• Hands-on experience in simulating signal processing algorithms in MATLAB and Python.
• Programming skills in C/C++.
• Experience in analyzing problems, identifying the right model architectures, developing models, training, and optimization, preferably in signal processing domains.

Preferred Qualifications

• Knowledge of CPU, DSP, or GPU architecture, as well as memory, I/O, and networking interfaces.
• Experience with programming latency-sensitive, real-time, multi-threaded applications on CPUs and one or more of GPUs, DSPs, or Vector processors.
• Appetite to learn the details of how next generations of GPU will operate and build an outstanding Software-Radio 5G/6G stack that can fully demonstrate their power.
• Familiarity with CUDA programming and NVIDIA GPU Architectures.