Job description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. NVIDIA has a rapidly expanding ecosystem of data center platform designs. From single node HGX/DGX systems all the way up to large multi-node NVLink domain rack architectures. These designs have become core to NVIDIA's rapidly growing enterprise and cloud provider businesses. Each brings together the full power of NVIDIA GPUs, NVIDIA NVLink, NVIDIA InfiniBand networking, NVIDIA Grace CPUs, and a fully optimized NVIDIA AI and HPC software stack. We are searching for a highly motivated engineer to lead performance benchmarking and optimization efforts for our data center products. You will be instrumental in ensuring our data center solutions deliver industry-leading performance for accelerated computing workloads. What you will be doing: • Design and execute comprehensive performance benchmarking strategies for our data center platforms and products • Characterize real-world AI training, inference, and HPC workloads at scale • Define, track, and report key performance indicators (throughput, latency, efficiency, scaling) • Build automation tools and frameworks for performance monitoring and analysis • Identify and analyze performance bottlenecks across compute, memory, network and storage subsystems • Work closely with architecture, hardware, software, networking, storage and customer teams to resolve performance issues • Drive performance improvements through system tuning, configuration optimization, and architectural recommendations for future generation systems What we need to see: • M.S. or Ph.D. in Computer Science, Electrical Engineering or related field (or equivalent experience). • 8+ years of experience in performance engineering or system architecture • Deep understanding of computer architecture, hardware-software interaction and computing at-scale • Strong proficiency in performance profiling tools (Linux perf, NVIDIA Nsight Systems) • Familiarity with GPU computing and parallel programming (CUDA) • Background with HPC networking technologies (InfiniBand, RoCE, NVLink) • Programming skills in Python, C++, and shell scripting. Excellent analytical and problem-solving abilities • Adaptability and passion to learn new technologies • Ability to communicate effectively and work with cross-functional global teams Ways to stand out from the crowd: • Experience with AI/ML frameworks (PyTorch, TensorFlow, JAX). Knowledge of MPI, collective communications (NCCL), distributed training and inference. Familiarity with NVIDIA DGX, HGX platforms and other data center solutions • Familiar with containers, cloud provisioning and scheduling tools (Docker, Kubernetes, SLURM). Understanding of storage systems and I/O performance • Track record of performance optimization in production environment. Experience with AI code generation tools Your base salary will be determined based on your location, experience, and the 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. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until September 23, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive 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.

Requirements

Must-haves

Design and execute comprehensive performance benchmarking strategies for our data center platforms and products
Characterize real-world AI training, inference, and HPC workloads at scale
Define, track, and report key performance indicators (throughput, latency, efficiency, scaling)
Build automation tools and frameworks for performance monitoring and analysis
Identify and analyze performance bottlenecks across compute, memory, network and storage subsystems
Work closely with architecture, hardware, software, networking, storage and customer teams to resolve performance issues
Drive performance improvements through system tuning, configuration optimization, and architectural recommendations for future generation systems
M.S. or Ph.D. in Computer Science, Electrical Engineering or related field (or equivalent experience).
8+ years of experience in performance engineering or system architecture
Deep understanding of computer architecture, hardware-software interaction and computing at-scale
Strong proficiency in performance profiling tools (Linux perf, NVIDIA Nsight Systems)
Familiarity with GPU computing and parallel programming (CUDA)
Background with HPC networking technologies (InfiniBand, RoCE, NVLink)
Programming skills in Python, C++, and shell scripting. Excellent analytical and problem-solving abilities
Adaptability and passion to learn new technologies
Ability to communicate effectively and work with cross-functional global teams
Familiar with containers, cloud provisioning and scheduling tools (Docker, Kubernetes, SLURM). Understanding of storage systems and I/O performance
Track record of performance optimization in production environment. Experience with AI code generation tools
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until September 23, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aipythonmldockerkubernetes

Platform: eightfold
Effort: medium

Benefits

Benefits detected in the listing.

Vision