Nvidia DGX Cloud Performance Engineer 

United States, California 

448315536

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 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

What we need to see:

• 7+ 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, …)

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 quickly

• Proficiency in CUDA, XLA

• Excellent interpersonal skills

• PhD nice to have