Senior DGX Cloud Performance Engineer
About The Position
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).
Requirements
- 12+ years of proven experience
- Ability to work with large scale parallel and distributed accelerator-based systems
- Expertise optimizing performance and AI workloads on large scale systems
- Experience with performance modeling and benchmarking at scale
- Strong background in Computer Architecture, Networking, Storage systems, Accelerators
- Familiarity with popular AI frameworks (PyTorch, TensorFlow, JAX, Megatron-LM, Tensort-LLM, VLLM) among others
- Experience with AI/ML models and workloads, in particular LLMs
- Understanding of DNNs and their use in emerging AI/ML applications and services
- Bachelors or Masters in Engineering (preferably, Electrical Engineering, Computer Engineering, or Computer Science) or equivalent experience
- Proficiency in Python, C/C++
- Expertise with at least one of public CSP infrastructure (GCP, AWS, Azure, OCI, …)
Nice To Haves
- Very high intellectual curiosity; Confidence to dig in as needed; Not afraid of confronting complexity; Able to pick up new areas quickly
- Proficiency in CUDA, XLA
- Excellent interpersonal skills
- PhD nice to have
Responsibilities
- 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 methodologies
- Collaborate with AI researchers, developers, and application service providers to understand difficulties, requirements, project future needs and share best practices
- Work 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 Cloud
Benefits
- With 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.
- You will also be eligible for equity and benefits.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Industry
Computer and Electronic Product Manufacturing
Number of Employees
5,001-10,000 employees
