PhD students in wireless communications and AI have a strong opportunity with the PhD Internship AI ML in Wireless L1/L2 (Spring 2026) at NVIDIA, Bengaluru, offering an estimated ₹6–8 LPA equivalent annualized package for the internship period. This SEO-focused post is tailored to attract advanced research scholars searching for NVIDIA PhD internships in India, AI/ML wireless internships, and Spring 2026 research roles.
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Table of Contents
Internship overview
The role is designed for PhD scholars working at the intersection of AI/ML and wireless physical/MAC layers (L1/L2), contributing to NVIDIA’s Aerial CUDA Accelerated RAN (ACAR) framework for 5G/6G.
- Company: NVIDIA
- Role: PhD Intern – AI/ML in Wireless L1/L2
- Location: Bengaluru, India
- Internship term: Spring 2026 (minimum 6 months, starting last week of January 2026)
- Compensation: Approx. ₹6–8 LPA (internship CTC equivalent based on monthly pay range for PhD interns in India)
- Team: Aerial RAN, AI-native wireless stack (Phy/MAC layers)
The internship places you inside NVIDIA’s advanced wireless research group working on AI-native 6G RAN and next‑generation radio access networks.
About the role and team
NVIDIA’s Aerial platform enables software-defined, cloud-native RAN on NVIDIA CPU/GPU/DPU systems, targeting high spectral and energy efficiency for future 6G networks. As a PhD intern, you help bring AI/ML into wireless L1/L2 signal processing blocks, enhancing over‑the‑air (OTA) performance while controlling compute complexity.
- Work with Aerial CUDA Accelerated RAN (ACAR) to build AI-native PHY/MAC functions.
- Collaborate with cross‑functional groups, including DevTech and other business units.
- Contribute to research‑grade prototypes that can influence commercial‑grade 5G/6G stacks.
This environment suits research-minded candidates who want both publications-level work and real product impact.
Key Responsibilities for PhD Internship AI ML
The internship focuses on designing, training, and integrating ML models into wireless signal-processing chains at L1/L2.
- Develop and optimize AI/ML modules for specific wireless signal-processing functional blocks in PHY/MAC.
- Perform literature surveys on AI/ML for RAN to understand prior art and state-of-the-art methods.
- Identify suitable ML architectures (e.g., Transformers, CNNs) for targeted RAN functions and tune their complexity.
- Benchmark OTA performance improvements and compute requirements across NVIDIA platforms.
- Iteratively train, test, and refine models for better performance under realistic wireless conditions.
You will translate theoretical models into deployable, latency‑aware AI components integrated with GPU‑accelerated stacks.
Required qualifications
The role is tailored specifically for full‑time PhD students already working in AI and wireless domains.
- Active full‑time PhD enrollment in AI/ML, Wireless Communications, Signal Processing, or related areas.
- Ability to intern for at least 6 months starting late January 2026.
- Strong understanding of wireless L1/L2 functions and algorithms (PHY/MAC).
- Solid grasp of AI and ML concepts, including latest techniques and architectures.
- Deep understanding of Transformers, CNNs, and other ML architectures and their application to signal-processing tasks.
- Hands‑on experience simulating signal‑processing algorithms in MATLAB and Python.
- Proficiency in C/C++ programming for performance‑critical implementations.
This mix of wireless fundamentals and cutting‑edge ML is essential to succeed in the role.
Preferred/bonus skills
Strong candidates can further stand out by bringing systems and hardware awareness to their ML work.
- Knowledge of CPU, DSP, GPU architectures, memory, I/O, and networking interfaces.
- Experience programming latency‑sensitive, real‑time, multi‑threaded applications on CPUs and GPUs/DSPs/vector processors.
- Familiarity with CUDA programming and NVIDIA GPU architectures.
- Prior work in AI for signal processing, RAN functions, or wireless simulations.
Such skills allow you to design ML models that are not only accurate but also deployment‑ready on NVIDIA platforms.
What you will learn
This PhD internship creates a bridge between academic research and industrial‑grade AI‑native wireless systems.
- End‑to‑end exposure to building AI‑enhanced PHY/MAC pipelines for 5G/6G.
- Practical experience in benchmarking OTA performance vs. compute costs on real hardware.
- Deeper understanding of GPU‑accelerated wireless stacks and cloud‑native RAN design.
- Collaboration with top engineers and researchers in AI, wireless, and systems inside NVIDIA.
For PhD scholars, this can directly feed into thesis work, publications, patents, and future full‑time roles.
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Application details and hiring window
The listing specifies Spring 2026 with start from the last week of January 2026 and a minimum 6‑month duration in Bengaluru. Compensation typically aligns with ₹6–8 LPA equivalent for high‑end PhD internships in India, although exact figures depend on NVIDIA’s internal pay bands and candidate profile.
To apply:
- Use NVIDIA’s official careers/university recruiting page and search for “PhD Intern, AI ML in Wireless L1/L2 – Spring 2026, Bengaluru”.
- Prepare a research‑focused CV, highlighting wireless/AI publications, projects, and toolchains like MATLAB, Python, PyTorch/TF, and C/C++.
- Tailor your cover letter to emphasize AI for RAN, 5G/6G interest, and L1/L2 expertise.
Early application is recommended as research internships are often filled on a rolling basis.
How To Apply?
If you are an Interested Candidate, you can apply for the PhD Internship AI ML in Wireless L1/L2 Spring 2026 Hiring at NVIDIA Bengaluru | ₹6-8 LPA Click Here.