NVIDIA DGX™ Cloud is an end-to-end, scalable AI platform for developers, offering scalable capacity built on the latest NVIDIA architecture and co-engineered with the world’s leading cloud service providers (CSPs). We are seeking highly skilled Parallel and Distributed Systems engineers to drive the performance analysis, optimization, and modeling to define the architecture and design of NVIDIA's DGX Cloud clusters. The ideal candidate will have a deep understanding of the methodology to conduct end to end performance analysis of critical AI applications running on large scale parallel and distributed systems. Candidates will work closely with the multi-functional teams to define DGX Cloud cluster architecture for different CSPs, optimize workloads running on these systems and develop the methodology that will drive the HW-SW codesign cycle to develop elite AI infrastructure at scale and make them more easily consumable by users (via improved scalability, reliability, cleaner abstractions, etc).What you will be doing:Develop benchmarks, end to end customer applications running at scale, instrumented for performance measurements, tracking, sampling, to measure and optimize performance of meaningful applications and services;Construct carefully designed experiments to analyze, study and develop critical insights into performance bottlenecks, dependencies, from an end to end perspective;Develop ideas on how to improve the end to end system performance and usability by leading changes in the HW or SW (or both).Collaborate with external CSPs during the full life cycle of cluster deployment and workload optimization to understand and drive standard methodologiesCollaborate with AI researchers, developers, and application service providers to understand difficulties, requirements, project future needs and share best practicesWork with a diverse set of LLM workloads and their application areas such as health care, climate modeling, pharmaceuticals, financial futures, Genomics/Drug discovery, among others.Develop the vital modeling framework and the TCO analysis to enable efficient exploration and sweep of the architecture and design space;Develop the methodology needed to drive the engineering analysis to advise the architecture, design and roadmap of DGX CloudWhat we need to see:12+ years of proven experienceAbility to work with large scale parallel and distributed accelerator-based systemsExpertise optimizing performance and AI workloads on large scale systemsExperience with performance modeling and benchmarking at scaleStrong background in Computer Architecture, Networking, Storage systems, AcceleratorsFamiliarity with popular AI frameworks (PyTorch, TensorFlow, JAX, Megatron-LM, Tensort-LLM, VLLM) among othersExperience with AI/ML models and workloads, in particular LLMsUnderstanding of DNNs and their use in emerging AI/ML applications and servicesBachelors or Masters in Engineering (preferably, Electrical Engineering, Computer Engineering, or Computer Science) or equivalent experienceProficiency in Python, C/C++Expertise with at least one of public CSP infrastructure (GCP, AWS, Azure, OCI, …)Ways to stand out from the crowd:Very high intellectual curiosity; Confidence to dig in as needed; Not afraid of confronting complexity; Able to pick up new areas quicklyProficiency in CUDA, XLAExcellent interpersonal skillsPhD nice to haveWith competitive salaries and a generous benefits package (www.nvidiabenefits.com ), we are 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 and, due to outstanding growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, 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 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 425,500 USD for Level 6.You will also be eligible for equity and benefits.Applications for this job will be accepted at least until September 14, 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.