PhD Intern, AI ML in Wireless L1/L2 - Fall 2026
NVIDIA is hiring a PhD Intern, AI ML in Wireless L1/L2 - Fall 2026 in Bengaluru, India. Level rates it ; you can apply on NVIDIA.
Level's read on this job
- On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
- The posting mentions Python, PyTorch and TensorFlow among its tools and skills.
- Level classes it as an internship.
- NVIDIA has 2,700+ other open roles on Level.
AI in this role
Develop and optimize AI/ML modules for wireless signal processing and 6G RAN stacks as a PhD intern.
Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams 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 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!
How we rate this
PhD Intern, AI ML in Wireless L1/L2 - Fall 2026 at NVIDIA rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where deep learning was part of your work. What did you do?
- Tell me about a project where wireless communication was part of your work. What did you do?
- Tell me about a project where signal processing was part of your work. What did you do?
- Tell me about a project where transformers was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Machine learning, Deep learning, Wireless Communication, Signal Processing, and Transformers. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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