Senior HPC Performance Engineer

Job Description

NVIDIA is seeking a motivated Performance Engineer to influence the roadmap of their communication libraries for Deep Learning and HPC applications.

Requirements

• M.S. or PHD in Computer Science or related field with relevant performance engineering and HPC experience
• 3+ yrs of experience with parallel programming and at least one communication runtime (MPI, NCCL, UCX, NVSHMEM)
• Experience conducting performance benchmarking and triage on large scale HPC clusters
• Good understanding of computer system architecture, HW-SW interactions, and operating systems principles
• Ability to debug performance issues across the entire HW/SW stack
• Proficient in a scripting language, preferably Python
• Experience with containers, cloud provisioning, and scheduling tools (Kubernetes, SLURM, Ansible, Docker)

Responsibilities

• Conduct in-depth performance characterization and analysis on large multi-GPU and multi-node clusters
• Study the interaction of libraries with all HW and SW components in the stack
• Evaluate proof-of-concepts and conduct trade-off analysis
• Triage and root-cause performance issues reported by customers
• Collect performance data and build tools to visualize and analyze information
• Collaborate with a dynamic team across multiple time zones

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