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Advanced Microdevices Pvt. Ltd. (India) · 2 months ago

Distributed Training Validations and Automation Engineer

San Jose, CA

Full-time

Hybrid

Mid, Senior Level

Advanced Micro Devices, Inc is a leading company in the computing industry focused on innovation and collaboration. They are seeking an AI solutions validation Engineer to validate AI solutions for distributed training and inference workloads, build automation for these tasks, and design groundbreaking technologies.

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Responsibilities

Work with AMD’s architecture specialists to validate AI solutions for distributed training and inference workloads with AMD's ROCM software

Build cluster scale automation for distributed training and inference workloads

Publish reference designs and benchmark numbers for AI workloads

Apply a data minded approach to target optimization efforts

Design and develop new groundbreaking AMD technologies

Participating in new ASIC and hardware bring ups

Develop technical relationships with peers and partners

Qualification

AI infrastructure validationDistributed training automationPerformance benchmarkingPython programmingKubernetesLinux operating systemEffective communicationProblem-solving skills

Required

Passionate about software engineering, system design, validation, automation

Possess leadership skills to drive sophisticated issues to resolution

Able to communicate effectively and work optimally with different teams across AMD

Work with AMD's architecture specialists to validate AI solutions for distributed training and inference workloads with AMD's ROCM software

Build cluster scale automation for distributed training and inference workloads

Publish reference designs and benchmark numbers for AI workloads

Apply a data minded approach to target optimization efforts

Design and develop new groundbreaking AMD technologies

Participating in new ASIC and hardware bring ups

Develop technical relationships with peers and partners

Preferred

Good experience with complex compute systems used in AI, HPC deployments, backend network designs in RDMA clusters

Experience in validating complex AI infrastructure - GPUs, networking, ROCEv2, UEC, running benchmark tests like IBPerf benchmarking, RCCL/NCCL

Experience with running training of LLMs, MoE models, Image Generation, recommendations models with different frameworks like PyTorch, Tensorflow, Megatron-LM, JAX. Running training performance benchmarks

Experience with running inference workloads in AI clusters with different inference frameworks like vLLM, SGLang. Running performance benchmarks for inference

Experience with distributed systems and schedulers like Kubernetes, Slurm

Ability to write high quality automation frameworks and scripts using Python or Golang

Experience with performance profiling of CPUs, GPUs and debugging complex compute, network, storage problems

Experience with AMD ROCM would be an added advantage

Experience with Linux, Windows operating systems

Effective communication and problem-solving skills

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