N

NVIDIA

Designs the chips and software that power AI

Senior Solutions Architect - CSP System

Systems Software EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • A Bachelor's, Master's, or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field; equivalent industry experience will be considered.
  • At least 7 years of hands-on experience in CPU architecture, performance optimization, or data center infrastructure, focused on high-performance computing or AI workloads.
  • Deep expertise in CPU microarchitecture, including x86 or ARM, performance analysis tools, and optimization methodologies, with a proven track record of CPU benchmarking and bottleneck-driven tuning.
  • Strong programming proficiency in C/C++ and/or Python, with experience in low-level software optimization, compiler toolchains, or performance libraries.
  • Proven experience working with major Chinese cloud service providers or global hyperscalers, and a deep understanding of their technical requirements, infrastructure, and workload characteristics.
  • Technical communication and presentation skills to explain complex CPU and system-level concepts to technical and non-technical stakeholders, including customers, executives, and internal teams.
  • Cross-functional collaboration skills to work effectively in a matrixed global team and manage multiple priorities in a fast-paced environment.
  • Hands-on ability is mandatory.

Responsibilities

  • Work with Sales, Business Development, and CPM teams to introduce NVIDIA technologies into assigned accounts and grow the business.
  • Serve as the primary technical authority on CPU technologies for NVIDIA’s Chinese cloud service provider customers, providing expert consultation on CPU selection, architecture design, and integration with NVIDIA’s AI infrastructure, including Grace and Vera CPUs and NVL72 platforms.
  • Lead CPU-focused technical engagements with cloud service providers, collaborating with their research and development, infrastructure, and AI teams to understand workload requirements such as AI data preprocessing, high-performance computing, and distributed computing, and design optimized CPU-GPU integrated solutions.
  • Drive CPU performance optimization for cloud service provider workloads by analyzing bottlenecks, implementing tuning strategies including SIMD instruction set optimization and low-level intrinsics, and delivering reference implementations.
  • Act as a liaison between cloud service provider customers and NVIDIA’s global engineering, product, and research and development teams, advocating for customer-specific CPU requirements, providing feedback on product roadmaps, and ensuring alignment with NVIDIA’s technical strategy and export compliance guidelines.
  • Lead technical workshops, training sessions, and proof-of-concept projects for cloud service providers, demonstrating NVIDIA’s CPU-integrated solutions and enabling customer teams to use the technologies effectively.
  • Monitor trends in CPU technology, data center architectures, and cloud service provider workload evolution, and provide strategic insights to internal teams to enhance NVIDIA’s CPU-related products and solutions for the Chinese market.
  • Mentor junior technical team members, share CPU expertise, and drive best practices in cloud service provider technical engagement and solution delivery.

Desired Qualifications

  • Familiarity with NVIDIA’s data center products, including GPUs, DPUs, and CPUs, and software stacks.
  • Understanding of AI factory concepts and large-scale data center deployment.
  • Experience developing Linux kernel and virtualization technologies, such as KVM/QEMU, hypervisors, device passthrough, SR-IOV, and VFIO, particularly for high-performance CPU-GPU-DPU platforms in virtualized and containerized cloud service provider environments.
  • Experience with NVIDIA Grace or Vera CPUs, other ARM-based high-performance CPUs, and integrated CPU-GPU-DPU platforms.
  • Experience with CPU in Agentic AI and post-training.
  • Background in AI/ML workload optimization, particularly data preprocessing, distributed training, or inference pipelines on CPU platforms.
  • Knowledge of export control regulations related to semiconductor and data center technologies, and experience navigating compliance requirements in the Chinese market.
  • Contributions to open-source performance tools, high-performance computing frameworks, or CPU optimization libraries.
  • Experience leading technical programs or cross-functional initiatives for cloud service provider customers, including proof-of-concept delivery and large-scale deployment support.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

Recently Posted Jobs

Explore more opportunities at NVIDIA

See more jobs