Senior HPC Performance Engineer

NVIDIA AI; Val-de-Travers; Vor Ort; CHF 120.000 - 180.000; Vollzeit

Zusammenfassung

NVIDIA AI in Switzerland seeks a performance engineer to drive optimization of HPC communication libraries and large-scale GPU workloads. You will characterize performance on multi-GPU clusters, study hardware-software interactions, and guide roadmap choices.

You will implement C/C++ micro-benchmarks, debug across HW/SW, and script with Python. Containers, Kubernetes, and SLURM enable scalable testing in a collaborative, global team.

Qualifikationen

• MS or PhD in Computer Science or related field with performance engineering and HPC experience.
• 3+ years of experience with parallel programming and a communication runtime (MPI, NCCL, UCX, NVSHMEM).
• Experience benchmarking and triaging performance on large HPC clusters.
• Strong understanding of computer system architecture and OS principles.
• Proficiency in C/C++ micro-benchmarks and code modification when required.
• Proficient in Python scripting and debugging performance issues across HW/SW.
• Familiar with containers and scheduling tools (Kubernetes, SLURM, Docker, Ansible).
• Willingness to learn new areas and collaborate across time zones.

Aufgaben

• Conduct in-depth performance characterization on large multi-GPU and multi-node clusters.
• Study interactions of libraries with hardware and software components in the stack.
• Evaluate concepts and perform trade-offs when multiple solutions exist.
• Triage and root-cause performance issues reported by users.
• Collect and analyze performance data; build visualization tools.
• Collaborate with a dynamic team across multiple time zones.

Kenntnisse

Parallel programming

MPI

NCCL

UCX

NVSHMEM

C/C++

Python scripting

Docker

Kubernetes

SLURM

Ansible

Ausbildung

MS or PhD in CS or related field

Tools

MPI

NCCL

UCX

NVSHMEM

C/C++

Python

Docker

Kubernetes

SLURM

Ansible

Jobbeschreibung

Job Requisition ID JR2001201 Job Category Engineering Time Type Full time NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. Come work for the team that brought to you NCCL, NVSHMEM & GPUDirect. Our GPU communication libraries are crucial for scaling Deep Learning and HPC applications! We are looking for a motivated Performance engineer to influence the roadmap of our communication libraries. The DL and HPC applications of today have a huge compute demand and run on scales which go up to tens of thousands of GPUs. The GPUs are connected with high-speed interconnects (eg. NVLink, PCIe) within a node and with high-speed networking (eg. Infiniband, Ethernet) across the nodes. Communication performance between the GPUs has a direct impact on the end-to-end application performance; and the stakes are even higher at huge scales! This is an outstanding opportunity for someone with HPC and performance background to advance the state of the art in this space. Are you ready for to contribute to the development of innovative technologies and help realize NVIDIA's vision?

What You Will Be Doing

• Conduct in-depth performance characterization and analysis on large multi-GPU and multi-node clusters.
• Study the interaction of our libraries with all HW (GPU, CPU, Networking) and SW components in the stack
• Evaluate proof-of-concepts, conduct trade-off analysis when multiple solutions are available
• Triage and root-cause performance issues reported by our customers
• Collect a lot of performance data; build tools and infrastructure to visualize and analyze the information
• Collaborate with a very dynamic team across multiple time zones

What We Need To See

• M.S. (or equivalent experience) 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 (aka systems software fundamentals)
• Implement micro-benchmarks in C/C++, read and modify the code base when required
• Ability to debug performance issues across the entire HW/SW stack. Proficient in a scripting language, preferably Python
• Familiar with containers, cloud provisioning and scheduling tools (Kubernetes, SLURM, Ansible, Docker)
• Adaptability and passion to learn new areas and tools. Flexibility to work and communicate effectively across different teams and timezones

Ways To Stand Out From The Crowd

• Practical experience with Infiniband/Ethernet networks in areas like RDMA, topologies, congestion control
• Experience debugging network issues in large scale deployments
• Familiarity with CUDA programming and/or GPUs
• Experience with Deep Learning Frameworks such PyTorch, TensorFlow

NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. For Poland: The base salary range is 221,250 PLN - 383,500 PLN for Level 3, and 292,500 PLN - 507,000 PLN for Level 4.