At AMD, the business problem is to accelerate next-generation computing experiences, from AI and data centers to PCs, gaming, and embedded systems, by building great products and solving the world's most important challenges through innovation and collaboration.
Requirements
- Experience with ML hardware architecture, software optimization, performance modeling and latest trend in inference and training.
- Experience in mapping model architecture to low level software, hardware and understanding the impact of each layer of the stack to model performance.
- Strong knowledge in latest generative model architecture, especially SoTA models, distributed inference and deployment at scale.
- Strong technical expertise and experience in performance analysis, projection, and hardware architecture.
- PhD or Master plus equivalent experience in computer science, electrical engineer, or a related field.
- 20+ years of experience leading a performance engineering team.
- Strong leadership skills, ability to work collaboratively with customers and cross-functional teams.
Responsibilities
- Set strategy and roadmap for AMD model optimization.
- Lead, mentor and scale a word class high performance team focused on ML workload optimization.
- Performance tuning, profiling and analysis of large-scale models for LLM, diffusion, multimodal, RecSys and generative AI, single node and distributed.
- Partner with the business, customer solution, and various engineering organizations to deliver the best performance across AMD GPUs.
- Participate in hardware-software co-design for future hardware optimization on various ML workloads.
- Develop and improve framework, tools and infrastructure for performance estimation, modeling and reporting.
- Communicate and present the results of the performance analysis and modeling to customers, stakeholders, and senior leadership.
Other
- A PhD or Master plus equivalent experience in computer science, electrical engineer, or a related field.
- 20+ years of experience leading a performance engineering team.
- Strong leadership skills, ability to work collaboratively with customers and cross-functional teams.
- Mentor, coach, and inspire a diverse and talented team of researchers and engineers.
- Excellent written, verbal, and presentation skills, ability to coordinate internally and externally.
