NVIDIA
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Senior Solutions Architect, HPC and AI
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NVIDIA Overview
NVIDIA is looking for a Field Escalation Solution Architect with experience in validation and debugging of large-scale GPU clusters focused on performance. As part of the Solution Architecture organization, we work with the most sophisticated computing hardware and software, driving the latest deep learning and machine learning breakthroughs with NVIDIA’s enterprise customers. This role offers an excellent opportunity to build your career in the rapidly growing field of deep learning while enabling the world's most successful technology companies. Primary responsibilities are to validate and debug customer cluster performance issues and functional bottlenecks, and to drive customer technical engagements around NVIDIA products and technologies. What You’ll Be Doing
A considerable part of the day-to-day job is staying up to date on pioneering High Performance Computing, Deep Learning and Machine Learning ecosystems. Architect and scale high-performance, distributed AI infrastructure on-prem or in the cloud built with the latest NVIDIA GPU supercomputers for new and existing customers. Address and resolve problems from the bare metal level up through the operating system, software stack, and application level. Share knowledge with different teams by delivering demos, assisting with proof-of-concepts, and writing papers and developer blogs. Collaborate with executives and engineering to address sophisticated problems and bring NVIDIA's premier technologies to life in the cloud and in the datacenter. Work directly with developers and hardware architects to debug cluster performance issues, identify new requirements, cross-train other account solution architects, and improve workflows. Engagement by the account team when extra analysis is required in debugging customer issues. Provide expertise to enable the account team to be more adaptable to the customer and product engineering, to obtain more actionable data rapidly. Build custom product demonstrations and proofs-of-concept for solutions addressing critical business needs of customers. What We Need To See
BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or other Engineering fields or equivalent experience. 8+ years of work-related experience in NVIDIA and/or accelerated computing technologies. Platform-level understanding of server architecture, PCIe topology, CPUs, GPUs, NICs, Linux OS, and kernel drivers. Networking experience with Ethernet, InfiniBand, or other networking protocols. Experience with DevOps on-prem or in cloud environments, including Docker/Containers, cloud APIs, IaaS, and data center deployments. SLURM, Kubernetes, and/or other job schedulers for use, deployment, and debugging. Deep understanding of dense data center design, including computing, storage, networking, cloud APIs, and IaaS. Strong analytical and problem-solving skills, with good written and verbal communication to collaborate across engineering, sales, marketing, product, and program management teams. Ways To Stand Out
Demonstrated CPU performance debugging experience. Excellent customer-facing skills and background. Platform design engineering, coding, and debugging skills including C/C++, Linux kernel, virtualization and drivers, profilers/performance analysis tools (CPU & GPU), telemetry. Familiarity with Grace/ARM CPU architecture, NVIDIA systems/SDKs (e.g., CUDA), NVIDIA Networking technologies (e.g., RoCE, InfiniBand), and switch interconnects. Understanding of Deep Learning and Machine Learning frameworks (TensorFlow or PyTorch), LLM, MLOps, DevOps, and cloud technologies with Docker/containers, Kubernetes, and data center deployments. We make extensive use of conferencing tools, and occasional travel (up to 20%) is required for on-site customer visits and data science conferences. With highly competitive salaries, a comprehensive benefits package, and an excellent engineering culture, NVIDIA is widely regarded as one of the technology industry's most desirable employers. Your base salary will be determined based on location, experience, and pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. Equity and benefits are also provided. Applications for this job will be accepted at least until October 4, 2025. NVIDIA is committed to fostering a diverse work environment and is proud to be an equal opportunity employer. We value diversity in our current and future employees and do not discriminate 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. JR2005154
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Senior Solutions Architect, HPC and AI
role at
NVIDIA Overview
NVIDIA is looking for a Field Escalation Solution Architect with experience in validation and debugging of large-scale GPU clusters focused on performance. As part of the Solution Architecture organization, we work with the most sophisticated computing hardware and software, driving the latest deep learning and machine learning breakthroughs with NVIDIA’s enterprise customers. This role offers an excellent opportunity to build your career in the rapidly growing field of deep learning while enabling the world's most successful technology companies. Primary responsibilities are to validate and debug customer cluster performance issues and functional bottlenecks, and to drive customer technical engagements around NVIDIA products and technologies. What You’ll Be Doing
A considerable part of the day-to-day job is staying up to date on pioneering High Performance Computing, Deep Learning and Machine Learning ecosystems. Architect and scale high-performance, distributed AI infrastructure on-prem or in the cloud built with the latest NVIDIA GPU supercomputers for new and existing customers. Address and resolve problems from the bare metal level up through the operating system, software stack, and application level. Share knowledge with different teams by delivering demos, assisting with proof-of-concepts, and writing papers and developer blogs. Collaborate with executives and engineering to address sophisticated problems and bring NVIDIA's premier technologies to life in the cloud and in the datacenter. Work directly with developers and hardware architects to debug cluster performance issues, identify new requirements, cross-train other account solution architects, and improve workflows. Engagement by the account team when extra analysis is required in debugging customer issues. Provide expertise to enable the account team to be more adaptable to the customer and product engineering, to obtain more actionable data rapidly. Build custom product demonstrations and proofs-of-concept for solutions addressing critical business needs of customers. What We Need To See
BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or other Engineering fields or equivalent experience. 8+ years of work-related experience in NVIDIA and/or accelerated computing technologies. Platform-level understanding of server architecture, PCIe topology, CPUs, GPUs, NICs, Linux OS, and kernel drivers. Networking experience with Ethernet, InfiniBand, or other networking protocols. Experience with DevOps on-prem or in cloud environments, including Docker/Containers, cloud APIs, IaaS, and data center deployments. SLURM, Kubernetes, and/or other job schedulers for use, deployment, and debugging. Deep understanding of dense data center design, including computing, storage, networking, cloud APIs, and IaaS. Strong analytical and problem-solving skills, with good written and verbal communication to collaborate across engineering, sales, marketing, product, and program management teams. Ways To Stand Out
Demonstrated CPU performance debugging experience. Excellent customer-facing skills and background. Platform design engineering, coding, and debugging skills including C/C++, Linux kernel, virtualization and drivers, profilers/performance analysis tools (CPU & GPU), telemetry. Familiarity with Grace/ARM CPU architecture, NVIDIA systems/SDKs (e.g., CUDA), NVIDIA Networking technologies (e.g., RoCE, InfiniBand), and switch interconnects. Understanding of Deep Learning and Machine Learning frameworks (TensorFlow or PyTorch), LLM, MLOps, DevOps, and cloud technologies with Docker/containers, Kubernetes, and data center deployments. We make extensive use of conferencing tools, and occasional travel (up to 20%) is required for on-site customer visits and data science conferences. With highly competitive salaries, a comprehensive benefits package, and an excellent engineering culture, NVIDIA is widely regarded as one of the technology industry's most desirable employers. Your base salary will be determined based on location, experience, and pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. Equity and benefits are also provided. Applications for this job will be accepted at least until October 4, 2025. NVIDIA is committed to fostering a diverse work environment and is proud to be an equal opportunity employer. We value diversity in our current and future employees and do not discriminate 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. JR2005154
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