We are seeking a self-motivated senior software engineer for the Aerial Algorithms team. This hire will spearhead the creation and improvement of RAN algorithms. This will include a focus on AI/ML technologies. This position offers the opportunity to work on technology for 5G and 6G networks, using NVIDIA's world-class compute platforms to advance the field of software-defined digital signal processing stack!
What you’ll be doing:
As a member of NVIDIA's Aerial team, you will guide the system build initiatives encompassing research, composition, and development of RAN algorithms within the realms of 5G/6G PHY and MAC-Scheduler, integrating innovative strategies like AI/ML, Deep Learning, and Raytracing. You will enable realization of algorithms in a GPU accelerated system, carefully assessing the design and implementation tradeoffs! We need someone who can effectively work with customers and ecosystem partners and support integration, system simulations, performance benchmarking, and optimizations.
What we need to see:
MS or PhD degree in Electrical Engineering, Computer Science or equivalent experience.
Minimum of 8 years relevant experience
We require proven theoretical knowledge of communication systems, communication theory, linear algebra, detection and estimation theory, baseband signal processing algorithms, and channel coding
We seek deep expertise in LTE/5G NR L1 (PHY) and L2 (MAC-scheduler) algorithms design and optimizations
Experience with wireless algorithm performance characterization and analysis
Wireless base station design, development, and commercialization experience
Experience building system models with Matlab, C/C++ and/or Python for algorithm design and link-level simulation
Solid knowledge of 3GPP 5G NR standard
Strategic context of Telecom Industry and Wireless technology evolution
Ways to stand out from the crowds:
Research experience in AI/ML and its applications to wireless applications
Demonstrated experience in software development for commercial RAN products
Knowledge of SIMD computing architecture
Background of GPU or CUDA programming
Knowledge of Wireless Protocols and E2E Deployment Architecture
Top Skills
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
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