NVIDIA Aerial CUDA Accelerated RAN (ACAR) is framework for building high-performance, software-defined, cloud-native Radio Access Network functions over NVIDIA CPU/GPU/DPU based systems, which will drive our AI native 6G solutions. We are seeking a self-motivated Intern to drive the adoption of AI/ML functions in the Phy and Mac layers of our Aerial SW. 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 stack to achieve the Spectral and Energy efficiency goals of 6G!
What you'll be doing:
As a member of 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 the suitable ML architecture for the RAN functions of interest.
Identify the right ML Architecture, complexity for each of the functional blocks
Collaborate with multi-functional teams to optimize the 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 Arch for performance improvements
What we need to see:
Full time PhD student doing research in the fields of AI and Wireless domains, and able to work as an Intern for at least 6 months or more starting from last week of January 2026
Thorough understanding of the wireless Layer1/Layer2 functions and algorithm aspects
Excellent grip on AI and ML concepts, techniques and abreast of 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 the problem, identifying the right model architectures. developing Models, Training and Optimization, preferably on signal processing domains
Ways to stand out from the crowd:
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 or 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
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!