Fellow - AI for Science & Enterprise Architect

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 ROLE: Seeking a visionary and deeply Technical Fellow to lead our AI for Science & Enterprise strategy—harnessing the power of artificial intelligence, machine learning, and high-performance computing to accelerate discovery across physics, engineering, and harnessing AIs power for the enterprise. This Fellow will ensure that our scientific enterprise is positioned at the frontier of AI-driven innovation while anticipating the performance and scale requirements of next-generation AI systems. This Fellow will serve as a principal scientific architect and thought leader responsible for end-to-end AI for Science & Enterprise strategies—from foundational model training and agent frameworks through to large-scale simulation integration, exascale deployment, and cross-disciplinary collaboration. They will work closely with computational scientists, HPC architects, AI engineers, ecosystem partners, government stakeholders, and business leaders to influence our future research roadmap and global impact. THE PERSON: The ideal candidate is a visionary technical leader who thrives at the intersection of AI, high performance computing, and the practical application of technology. They combine technical depth with strategic foresight, able to translate emerging AI technologies into transformative outcomes. They are curious, collaborative, impact-driven, resilient, and adaptive. KEY RESPONSIBILITIES: Own the strategic vision for AI-driven scientific discovery, spanning LLM post-training, multi-agent systems, inverse design, and HPC-integrated AI workflows. Lead efforts to deploy AI on exascale and advanced accelerator platforms—designing scalable architectures and robust benchmarks for scientific & enterprise workloads. Guide organizational engagements with national and international consortia, standards groups, and funding agencies to advance AI for Science. Collaborate with laboratory, academic, and industry partners to deliver reference architectures and AI-enabled scientific pipelines in physics, materials, energy, and beyond. Serve as a global ambassador for AI for Science & Enterprise, shaping conversation in high-profile forums and contributing to joint solution roadmaps. Mentor senior scientists and engineers, fostering deep technical rigor, breakthrough research, and broad community impact. Contribute to IP strategy, whitepapers, and publications aligned to long-term AI for Science leadership. PREFERRED EXPERIENCE: Ph.D. in physical sciences, computer science, or a related field, with a record of impactful research. Proven leadership applying AI and high-performance computing to scientific, engineering or business problems. Experience defining and executing technology strategy across multidisciplinary teams or organizations. Demonstrated experience in developing or deploying large-scale AI models or agent systems in HPC environments. Recognition through fellowships, major scientific awards, or invited talks in AI or computational science. ACADEMIC CREDENTIALS: List any desired degrees, certifications, etc. Use the words preferred or desired, instead of required #LI-AG1 #LI-HYBRID Benefits offered are described: AMD benefits at a glance. 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.

Benefits offered are described: AMD benefits at a glance. 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.

THE ROLE: Seeking a visionary and deeply Technical Fellow to lead our AI for Science & Enterprise strategy—harnessing the power of artificial intelligence, machine learning, and high-performance computing to accelerate discovery across physics, engineering, and harnessing AIs power for the enterprise. This Fellow will ensure that our scientific enterprise is positioned at the frontier of AI-driven innovation while anticipating the performance and scale requirements of next-generation AI systems. This Fellow will serve as a principal scientific architect and thought leader responsible for end-to-end AI for Science & Enterprise strategies—from foundational model training and agent frameworks through to large-scale simulation integration, exascale deployment, and cross-disciplinary collaboration. They will work closely with computational scientists, HPC architects, AI engineers, ecosystem partners, government stakeholders, and business leaders to influence our future research roadmap and global impact. THE PERSON: The ideal candidate is a visionary technical leader who thrives at the intersection of AI, high performance computing, and the practical application of technology. They combine technical depth with strategic foresight, able to translate emerging AI technologies into transformative outcomes. They are curious, collaborative, impact-driven, resilient, and adaptive. KEY RESPONSIBILITIES: Own the strategic vision for AI-driven scientific discovery, spanning LLM post-training, multi-agent systems, inverse design, and HPC-integrated AI workflows. Lead efforts to deploy AI on exascale and advanced accelerator platforms—designing scalable architectures and robust benchmarks for scientific & enterprise workloads. Guide organizational engagements with national and international consortia, standards groups, and funding agencies to advance AI for Science. Collaborate with laboratory, academic, and industry partners to deliver reference architectures and AI-enabled scientific pipelines in physics, materials, energy, and beyond. Serve as a global ambassador for AI for Science & Enterprise, shaping conversation in high-profile forums and contributing to joint solution roadmaps. Mentor senior scientists and engineers, fostering deep technical rigor, breakthrough research, and broad community impact. Contribute to IP strategy, whitepapers, and publications aligned to long-term AI for Science leadership. PREFERRED EXPERIENCE: Ph.D. in physical sciences, computer science, or a related field, with a record of impactful research. Proven leadership applying AI and high-performance computing to scientific, engineering or business problems. Experience defining and executing technology strategy across multidisciplinary teams or organizations. Demonstrated experience in developing or deploying large-scale AI models or agent systems in HPC environments. Recognition through fellowships, major scientific awards, or invited talks in AI or computational science. ACADEMIC CREDENTIALS: List any desired degrees, certifications, etc. Use the words preferred or desired, instead of required #LI-AG1 #LI-HYBRID