PREFERRED EXPERIENCE:

• Deep experience optimizing large-scale ML systems and GPU architectures
• Strong track record of technical leadership in GPU performance and workload analysis including patents and recent publications, participation in industry forums and peer acknowledgement
• Deep expertise in CUDA programming, GPU memory hierarchies, and hardware-specific optimizations
• Proven track record architecting distributed training systems handling large scale systems
• Expert knowledge of transformer architectures, attention mechanisms, and model parallelism techniques

WHAT YOU DO AT AMD CHANGES EVERYTHING

We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives.
AMD together we advance_

THE ROLE:

As a Fellow/ Sr Fellow level Engineer you will spearhead performance analysis and modeling for AMD datacenter GPUs. You will lead efforts that enable massive model training at scale. Your expertise will lead teams to drive performance gains in both training and inference pipelines through innovative system design and optimization. You will champion adoption of cutting-edge techniques across the engineering organization. This role requires deep understanding of GPU microarchitecture, memory hierarchies, and their impact on large-scale ML workloads.