GPU Performance Attainment Engineer - ML and HPC Applications

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 TEAM:

AMD's Data Center GPU 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 Centers, (AI) Artificial Intelligence, HPC and Embedded systems. If this resonates with you, come and join our Data Center GPU organization where we are building amazing AI powered products.

THE ROLE:

As a senior member of the pre-silicon performance attainment team, you will be a technical contributor that drives end-to-end delivery of solutions, directly contributing to, and coordinating workload optimization across multiple teams for inference and training of machine learning models. You will collaborate closely with software and hardware teams to plan, develop and optimize use cases. This is an exciting opportunity to work at the cutting edge of GPU computing, influencing design and software strategies to power future datacenter AI and ML deployments.

THE PERSON:
We are seeking a passionate problem solver driven by real-world GPU performance challenges in datacenter environments. The ideal candidate will have hands-on expertise in pre-silicon performance analysis, debugging, and optimization of GPU architectures. Strong communication skills are essential, with the ability to clearly convey complex technical concepts and influence decisions across multiple organizational levels. This role demands a proactive individual eager to push the boundaries of GPU performance for AI and ML workloads through innovative, data-driven solutions. We value strategic thinkers with strong analytical skills who thrive in collaborative team environments, adapt quickly, and leverage collective strengths to develop impactful, cutting-edge solutions.

KEY RESPONSIBLITIES:

• Debug performance issues and analyze data from the full-chip Emulation Platform, RTL Simulator, and Architecture and Roofline Models.
• Analyze model projection results and identify algorithm issues to find novel solutions for improving the accuracy of projection for different families of products, and over multiple generations.
• Get performance projections for kernels using an analytical model. Identify efficiency issues and work with model owners to resolve performance projection shortcomings.
• Identify technical problems, break them down, summarize multiple possible solutions, and help the team to make progress.
• Automate processes related to performance infrastructure and data collection tasks, to enhance productivity and refine processes for improved efficiency.
• Engage with the workloads team to acquire and align on required workloads, run the selected workload traces on the performance simulator, analyze the performance results and metrics to root cause any anomalies.
• Collaborate with simulator team to bridge gaps between the performance numbers and the performance targets.
• Influence design trade-offs and optimizations by working closely with compiler, driver, library, and hardware engineers to achieve the highest performance for selected workloads.
• Innovate new algorithmic improvements that exploit the strengths of the hardware architecture to deliver the best possible machine learning performance.

PREFERRED EXPERIENCE:

• Several years of experience in GPU pre-silicon performance analysis and debug.
• Proficiency with performance modeling and simulation tools.
• Strong understanding of GPGPU programming APIs and Machine Learning workloads.
• Expertise in C/C++ /Scripting (Python, Perl, Shell etc.).
• Experience with hardware description languages such as Verilog is a plus.
• Familiarity with the software stack is a plus, preferably related to GPUs-such as applications, drivers, compilers, and firmware.

ACADEMIC CREDENTIALS:

• Bachelor's or higher degree in Computer Science, Electrical Engineering, or a closely related field.

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AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants' needs under the respective laws throughout all stages of the recruitment and selection process.