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AMD · 4 hours ago

Cluster Performance Engineer

Austin, TX

Full-time

Onsite

Mid, Senior Level

AMD is a company focused on building innovative products that enhance computing experiences across various domains. The Cluster Performance Engineer will work on optimizing AI clusters and multi-node GPU communication, collaborating with engineers to enhance performance and resolve system-level issues.

Artificial Intelligence (AI)Cloud ComputingComputerEmbedded SystemsGPUHardwareSemiconductor

Growth Opportunities

No H1B

Responsibilities

Become the liaison between the AMD engineers that work at the GPU, CPU and NIC components to help integrate solutions at the server-level, rack-level and cluster-level

Support validation of servers with AMD CPU/GPU/NICs and AMD’s libraries such as RCCL

Design, implement, and test networking features for multi-GPU and multi-node communication libraries, both scale-up and scale-out

Benchmark, profile and optimize code to maximize throughput on single-GPU, multi-GPU and clustered systems

Deploy the libraries on large clusters and debug complex system level issues that could span across different layers of the software stack: particularly NIC kernel driver and GPU kernel drivers

Qualification

GPU communication optimizationMulti-node GPU systemsNetworking features designCollective communication librariesLinux kernel experienceGPU software developmentCluster infrastructure optimizationAttention to detailWritten communicationVerbal communicationResults-oriented

Required

Bachelor's degree in Computer Science, Software Engineering, Electrical Engineering, or equivalent

Preferred

Enabling clusters for end users, finding and resolving problems

Experience working with RoCE(RDMA over Converge Ethernet), Libfabric and InfiniBand among others

Experience working with Linux Kernel, Device drivers and network drivers

Experience designing and building GPU Networks for Large Scale Clusters

Experience in collective communication libraries: MPI, RCCL, SHMEM and optimization to scale collective communication to scale distributed systems

In-depth knowledge of best practices in software development, including testing, profiling, debugging, documentation, version control, issue tracking, and planning

Contributions to open-source libraries and applications

Experience with installation and management of operating systems. Fundamental knowledge of virtual machines and hyper-visors

GPU software development using HIP, CUDA, or OpenCL

Understanding of CPU, GPU and NIC architecture and low-level optimization techniques including assembly programming and/or vectorization