NVIDIA has been defining computer graphics, PC gaming, and accelerated computing for more than 25 years. With an outstanding legacy of innovation, driven by phenomenal technology and extraordinary people, NVIDIA is looking for a Distinguished Engineer to help shape the future of AI infrastructure. As part of our advanced development and research efforts, you will drive technical vision and innovation across the AI software stack, spanning GPU computing, RDMA, NVLink, storage, and large-scale distributed systems. You will research next-generation system designs, influence product and platform direction, and help define how massive-scale AI environments are built, optimized, and operated through hardware-software co-design.
What you’ll be doing:
- Research, define, and drive co-design solutions across AI software stacks involving GPU computing, RDMA networking, NVLink interconnects, storage, and large-scale distributed infrastructure
- Lead deep technical investigations and proof-of-concept development in areas related to distributed AI, deep learning systems, high-performance computing, virtualization, memory management, and large-scale systems design
- Work closely with multiple teams across NVIDIA to advance next-generation AI infrastructure technologies and influence cross-stack co-design decisions
- Analyze end-to-end system bottlenecks and opportunities across compute, networking, memory, and storage layers to improve performance, scalability, and efficiency
- Guide the design of environments that support massive-scale AI training and inference workloads in production
What we need to see:
- M.Sc. or Ph.D. in Computer Science, Electrical Engineering, Computer Engineering, or equivalent experience
- 20+ years of industry experience in systems design, distributed systems, system software, or related fields
- Chief Scientist, CTO, or equivalent senior technical leadership experience in smaller companies is highly desirable
- Deep background in distributed systems, parallel computation, networking, storage, virtualization, and memory management
- Experience building, scaling, and supporting environments for massive AI workloads
- Strong understanding of large-scale systems operational aspects, including performance, reliability, scalability, and supportability
- Excellent communication, collaboration, and technical leadership skills in a multi-national, multi-time-zone environment
Ways to stand out from the crowd:
- Proven research track record in AI systems, large-scale infrastructure, or advanced systems co-design
- Deep expertise in GPU systems, RDMA, NVLink, and storage technologies for AI and HPC workloads
- Strong record of cross-functional influence spanning hardware, system software, networking, and infrastructure
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, autonomous, and excited to drive the future of AI infrastructure at scale, we want to hear from you!
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate, including in our hiring and promotion practices, on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.
Skills Required
- M.Sc. or Ph.D. in Computer Science, Electrical Engineering, Computer Engineering, or equivalent experience
- 20+ years of industry experience in systems design, distributed systems, system software, or related fields
- Deep background in distributed systems, parallel computation, networking, storage, virtualization, and memory management
- Experience building, scaling, and supporting environments for massive AI workloads
- Strong understanding of large-scale systems operations, including performance, reliability, scalability, and supportability
- Excellent communication, collaboration, and technical leadership skills in multinational, multi-time-zone environments
- Chief Scientist, CTO, or equivalent senior technical leadership experience in smaller companies
- Proven research track record in AI systems, large-scale infrastructure, or advanced systems co-design
- Deep expertise in GPU systems, RDMA, NVLink, and storage technologies for AI and HPC workloads
- Strong record of cross-functional influence spanning hardware, system software, networking, and infrastructure
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Company stock and RSUs have driven exceptional total compensation, with a generous employee stock purchase plan and ongoing equity refreshers playing a central role. Feedback suggests historic share-price gains created significant financial upside for many.
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Healthcare Strength — Multiple plan options (HSA, PPO, and in some locations Kaiser) with in-network preventive care covered at 100% and company HSA contributions indicate a robust offering. Mental-health sessions and broad dental, vision, and disability coverage further strengthen the package.
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Parental & Family Support — Up to 22 weeks of fully paid parental leave, adoption and surrogacy reimbursement, and coverage for IVF and egg freezing are highlighted as standout features. Additional family-care resources and caregiving support broaden the appeal.
NVIDIA Insights
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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