NVIDIA is actively seeking an outstanding Software engineer for Spectrum Ethernet Switch/SmartSwitch SONiC Group. As part of this team, candidates will engage with SONiC, a collaborative open-source initiative spearheaded by CSPS and numerous vendors, which enables a single network operating system to operate seamlessly across diverse ASICs and platforms. Notably, NVIDIA has been a major contributor to SONiC since its inception, and our technology is already powering Ethernet Switches, DPUs, and soon BMCs, making SONiC an integral component in RDMA and AI datacenter environments.
Renowned for fostering innovation and embracing forward-thinking talent, NVIDIA is consistently recognized as one of the most desirable employers in the tech industry. Our engineering teams are expanding rapidly due to remarkable growth, and we are eager to connect with creative, independent engineers who are passionate about technology and ready to take on new challenges.
What you'll be doing:
As Software Tech lead, candidates will lead technical discussion with Arch and customers, POC for new initiative and lead complex programs within and beyond the group.
Collaboration will be key, as the role involves working closely with various design and verification teams, architects, product marketing professionals.
What we need to see:
The ideal candidate will possess a B.Sc. in Software, Computer, Electrical, or Communication Engineering, or equivalent experience
Bring at least 12 years of overall experience, initiating, and leading features.
Hands-on proficiency in C, C++, and Python development is essential.
Great communication and presentation skills.
In-depth knowledge of Linux usage and internals.
Combined with creativity, motivation, and a strong value-driven mindset.
Ways to stand out from the crowd:
Expertise in leading both software and hardware integrations, as well as embedded software development.
Familiarity with routing protocols such as BGP, EVPN, and SRv6.
Familiarity with a variety of software development tools and methodologies, including AI tools.
Ability to dive deep into technical details, providing insightful guidance on features and bug resolution.
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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.”
