Full Description

WHAT YOU DO AT AMD CHANGES EVERYTHING At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career.

THE ROLE

• AMD is looking for an AI solutions validation Engineer who is passionate about complex AI solutions, AI infrastructure, building cluster scale automation for distributed training and inference workloads, MLOps. You will be a member of a core team of incredibly talented industry specialists and will work with the very latest hardware and software technology.

THE PERSON

• The ideal candidate should be passionate about software engineering, system design, validation, automation and possess leadership skills to drive sophisticated issues to resolution. Able to communicate effectively and work optimally with different teams across AMD.

KEY 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
• Reproduce field defects and develop appropriate tests to prevent future issues.
• Design, develop and deploy testing tools and automation libraries necessary to perform testing.
• Lead the adoption of tooling and industry best practices by means of advocacy and outreach to help our development communities level up.
• Other duties as assigned

PREFERRED EXPERIENCE

Languages: Python, C, C++, Linux Shell scripting.

Frameworks/Libraries: TensorFlow, PyTorch, ONNXRT

Tools: Prior experience with Linux, Docker, Kubernetes,SLURM, LLVM compilers Good experience with complex computer 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 performance profiling of CPUs, GPUs and debugging complex compute, network, storage problems. 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.