Senior DGX Cloud Performance Engineer

Job Description

NVIDIA is seeking Parallel and Distributed Systems engineers to work on optimizing performance and modeling for DGX Cloud clusters.

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, …)

Responsibilities

• Develop benchmarks and end-to-end customer applications running at scale
• Construct experiments to analyze and optimize performance
• Collaborate with multi-functional teams to define DGX Cloud cluster architecture
• Collaborate with external CSPs during cluster deployment and workload optimization
• Collaborate with AI researchers, developers, and application service providers
• Work with a diverse set of LLM workloads in various application areas
• Develop modeling framework and TCO analysis for architecture and design exploration

Benefits

• Multiple relocation packages
• Two weeklong shutdowns (mid-summer and year-end) in the US (in addition to PTO)
• 8-week parental leave
• 9 Employee Resource Groups
• Annual bonus offering
• Flexible work arrangements
• Up to 6% 401K matching