CVP, Data Center GPU Performance Architecture
Role details
Job location
Tech stack
Job description
We are seeking a Vice President of DGPU hw/sw architecture performance expert to drive the workload performance analysis/optimization of AMD's instinct GPU products. This position will lead and work with a team of engineers and performance architecture analysis experts to drive next generation instinct product performance architecture with learnings from customer workload competitive analysis., * Lead the datacenter GPU performance analysis/optimization team and engage with customer partners on strategic and tactical engagements.
- Build and maintain relationships with key partners and customers to drive business growth.
- Collaborate with cross-functional teams to provide deep competitive analysis and customer workload sensitivities to improve AMD's instinct product roadmap
- Build and manage a world-class team of technical leaders and performance analysis experts to deliver high-quality GPU/AI products.
- Drive technical innovation and excellence within the team, staying up-to-date with the latest advancements in architectures and silicon., AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD's "Responsible AI Policy" is available here.
Requirements
This candidate will have proven experience working on development and deployment of GPU/AI processors. We are looking for a unique leader with deep datacenter performance architecture expertise and understanding of the GPU and/or AI processor space, trends and someone that can build and scale a world-class team. Ideal candidate will have strong background in performance model development, workload characterization/analysis, competitive industry trends, AI/ML model development and hw/sw co-optimization., * Multiple years of experience in design and development of GPU/AI processors
- Strong architecture experience and insights that are needed to deliver industry-leading products
- Proven track record of leading successful performance architecture teams, delivering high performance products on time and within budget.
- Strong understanding of the GPU landscape, including AI trends, competitive landscape, and emerging technologies.
- Working knowledge of AI/ML workloads/models, software stack optimization, hw/sw design co-optimization.
- Excellent communication and leadership skills, with the ability to work with cross-functional teams.
ACADEMIC CREDENTIALS:
MS or PhD in Electrical/Computer Engineering, Computer Science, or a related field