NVIDIA is in search of a highly skilled Senior Storage Performance Engineer to join our ambitious team in Santa Clara, CA. This role is essential as we continue to push the boundaries of AI and HPC technologies. You will have the chance to create, implement, and analyze complex benchmarks to optimize performance across NVIDIA’s infrastructure stack. Your efforts will directly impact the efficiency and success of our AI inference and training, NVIDIA NIMs, RAG pipelines, HPC codes, and storage platforms, contributing significantly to our innovative journey.​What you'll be doing:Crafting and delivering performance benchmarks across AI, HPC, and enterprise storage platforms.Testing and benchmarking storage appliances (block, file, object) against NVIDIA data center solutions.Operating and adjusting AI inference and training workloads with tools like PyTorch, TensorFlow, and NVIDIA NIMs.Benchmarking and analyzing retrieval-augmented generation (RAG) pipelines, including ingestion, retrieval, and inference performance with vector databases.Profiling and optimizing MPI-based and multi-node distributed applications.Collaborating closely with product managers, system architects, and partners to fine-tune hardware/software stack performance.What we need to see:12+ years of experience in performance engineering, benchmarking, or HPC/AI systems.Deep expertise in AI/ML and deep learning frameworks (PyTorch, TensorFlow, Triton).Strong background in storage systems and filesystems.Proven experience with MPI, OpenMP, and Slurm in large-scale compute environments.Proficiency in Python, Bash, and automation frameworks for job orchestration and results parsing.Excellent communication skills; ability to context-switch between deep technical work and high-level business impact.BS, MS, or PhD or equivalent experience in Computer Science, Electrical Engineering, or related field. Ways to stand out from the crowd:Experience with RAG pipelines and vector databases (FAISS, Milvus, Qdrant).Familiarity with Kubernetes and CSI-based persistent storage systems.Knowledge of GPU profiling tools (Nsight Systems, PyTorch Profiler).Experience with telemetry/monitoring frameworks (Prometheus, Grafana).Enthusiastic about exploring the boundaries of AI, HPC, and storage capabilities!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 and autonomous, we want to hear from you!Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 200,000 USD - 322,000 USD.You will also be eligible for equity and benefits.Applications for this job will be accepted at least until September 29, 2025.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.