Software Advanced Development Engineer

Overview

• The NVIDIA Networking Advanced Development Software team develops new groundbreaking technologies to enable new market shares for the company and tighten customer relationships.
• These are emerging technologies in networking and distributed computing for the booming AI factories and data centers.
• They span areas such as AI neural networks, Deep Learning, High Performance Computing (HPC), Storage, Cloud, SW Defined Network, Network Function Virtualization and more.
• We develop the solutions top-down, all the way from application behavioral analysis, to architecture definition and down to the implementation, using the world-leading NVIDIA devices.
• The development traverses any needed component - application SW, middleware SW, OS kernel subsystems, device drivers, embedded SW (Firmware) and CUDA GPU.
• We collaborate with partners and key customers in the analysis processes and engage with open source communities introducing our leading features.
• What you’ll be doing: Design and implement solutions throughout all layers from high level application, OS and driver subsystem to firmware Work on impactful projects involving state-of-the-art high-performance computing hardware and software Provide insight and technical guidance and collaborate with peers from across the company - including software architecture, chip architecture, and engineering departments to improve our future technology Collaborate with NVIDIA partners and customers What we need to see: B.Sc.
• in Computer Science, Electrical Engineering, Computer Engineering, or a related field 3+ overall years of industry experience in system programming or related fields.
• Understanding of multi core hardware, operating systems design, concurrency, virtual memory, caching, interrupts, device drivers, real-time Excellent programming skills Ability to learn complex concepts in a fast pace environment.
• A teammate with a can-do attitude, high energy and excellent interpersonal skills Ways to stand out from a crowd: Familiarity with networking protocols Hands-on experience with CUDA programming and GPU acceleration Hands-on experience with LLM serving frameworks Experience with open-source projects (coursework, personal, or contributions) Working in a fast-paced and dynamic environment.