DC-GPU Performance Modeling Engineer

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.

DC-GPU Performance Modeling Engineer

 

The Team

AMDs Data Centre GPU Performance organization is transforming the industry with our AI based Graphic Processors. Our primary objective is to design exceptional products that drive the evolution of computing experiences, serving as the cornerstone for enterprise Data Centres for AI/ML workload.

The Role

Architect, analyse and optimize high-performance GPU-centric SoCs for Machine Learning workload. Develop performance models and methodologies. Propose solutions to enhance performance and optimize power for next-generation data centre systems.

The Person

As a system performance architect on our design engineering team, you will help propose and implement solutions to our next generation GPU SoCs and optimize data centre system application performance.

Key Responsibilities

• Define, build and maintain performance models for performance projections, analysis and architecture exploration.
• Develop and execute system-level modelling strategies for ML and GPU hardware and software co-design.
• Drive performance trade-off studies for new architectural features, algorithms, and system configurations, providing data-driven recommendations.
• Collaborate with architecture, design and software teams to integrate models, define workloads and analyse simulation results.
• Innovate and advance modelling methodologies, tools and infrastructure to improve accuracy, speed, and architectural insight.
  
  
  

• Strong understanding of computer architecture. Experience of working in GPUs, SoCs, ML accelerators would be a plus.
• Experience with performance analysis, workload characterization, and hardware/software co-design exploration.
• Familiarity with ML models and software stacks relevant to ML
• Understanding of AI model distributed training and inference, model layers and ML ops, parallelization strategies
• Experience in system-level modelling and simulation will be a plus.
• Strong programming skills, including experience with Python (or similar)
  
  
  

• Ph.D. in Computer Science / Electronics Engineering, and 3+ years of experience as a Performance Engineer
• M.S./M.Tech. in Computer Science / Electronics Engineering, and 5+ years of experience as a Performance Engineer
• B.Tech. in Computer Science / Electronics Engineering, and 7+ years of experience as a Performance Engineer