Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 6
Algorithms @ 6
CUDA @ 2
Communication @ 6
GPU @ 2
Machine Learning
Matlab @ 3
Python @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, NVIDIA is using AI and accelerated computing to define the next era of computing, with GPUs powering computers, robots, and self-driving cars.
The Aerial PHY team works on core wireless technology for next-generation 5G and 6G networks. The team builds high-performance software for the physical layer of the radio access network, using GPUs to accelerate signal-processing tasks such as coding, decoding, MIMO, and real-time data handling. This work turns advanced research into deployable platforms for commercial networks and future 6G innovation.
Responsibilities
- Develop an end-to-end reference system stack for 5G/6G baseband.
- Build and simulate algorithms for the 5G/6G PHY layer using MATLAB and Python.
- Implement and optimize PHY features in C, C++, and CUDA on a GPU platform based on 5G/6G specifications.
- Support system integration, performance testing, system demonstrations, and laboratory trials for end-to-end systems.
Requirements
- Pursuing a PhD or MS in Electrical and Computer Engineering, Electrical Engineering, Computer Science, or a related field.
- Strong background in classic and AI/ML-based algorithms for communication signal processing in wireless systems.
- Good understanding of the balance between algorithm performance and implementation cost.
- Programming skills in MATLAB/Python and C/C++.
Preferred Qualifications
- Familiarity with CUDA programming and NVIDIA GPU architectures.
- Familiarity with 3GPP, O-RAN, and FAPI standards related to 5G/6G.
Applicants should have excellent analytical ability and be passionate and highly motivated about solving complex engineering problems.
The internship hourly rate is USD 20–71, based on position, location, year in school, degree, and experience. Intern benefits are also available. Applications will be accepted at least until October 24, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.