at AMD
Location
San Jose, California
Compensation
$256k–$438k USD
Type
full time
Posted
5 months ago
Market range · company + function + seniority
p25 · target · p75 · n=37
Posted $438k · well above market
Posting health
Aging · 65Tailor your résumé to this role in 30 seconds.
Free account · ATS keyword check · per-job bullet rewrite by Claude.
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.
We are seeking an exceptional Senior Fellow in Engineering to serve as a technical leader for Machine Learning workload performance and optimization across frameworks and model architectures. This is a highly visible individual contributor (IC) role with broad technical scope and company-wide impact, operating at a level equivalent to Senior Director while focusing primarily on deep technical leadership rather than organizational management.
As Senior Fellow of ML workload performance, you will define and drive the technical vision for performance optimization across multiple generations of AMD GPUs, spanning a wide range of models including state-of-the-art AI systems. You will lead through influence, setting direction for optimization strategies, guiding architectural decisions, and accelerating support for emerging models.
You will work closely with customers, business units, and engineering teams to develop performance projections, conduct deep analysis, and deliver innovative solutions that meet partner needs. You will also play a key role in industry-standard benchmarks and external technical engagements.
This role is ideal for a hands-on technical leader who is passionate about extracting maximum performance from hardware and shaping the future of AI acceleration.
The ideal candidate is a recognized technical expert with a strong track record of driving large-scale performance optimization initiatives in ML systems. You bring deep expertise in ML hardware architecture, software optimization, and performance modeling, along with a strong understanding of how model architectures map to low-level software and hardware execution.
You are comfortable operating across the full stack—from model design to kernel-level optimization—and understand the performance implications at each layer. You influence without authority, mentor senior engineers, and provide technical direction across multiple teams.
Strong knowledge of modern generative model architectures, including state-of-the-art LLMs, diffusion models, and multimodal systems, as well as distributed inference and large-scale deployment, is essential.
KEY RESPONSIBILITIES:
Define and drive the technical strategy and roadmap for ML model optimization across AMD platforms.
Serve as the highest-level technical authority in performance optimization, guiding architecture, and implementation decisions.
Lead performance tuning, profiling, and analysis of large-scale models (LLMs, diffusion, multimodal, RecSys, generative AI) across single-node and distributed environments. · Drive hardware-software co-design initiatives to influence future GPU architectures and system-level optimizations.
Collaborate across engineering, research, and customer-facing teams to deliver best-in-class performance.
Develop advanced methodologies, tools, and infrastructure for performance estimation, modeling, and benchmarking.
Provide technical mentorship to senior engineers and influence best practices across the organization.
Represent AMD in external technical forums, benchmarks, and customer engagements. · Communicate complex technical findings and recommendations to senior leadership and stakeholders.
PREFERRED EXPERIENCE:
Sr. Fellow level of experience in performance engineering, ML systems, or related domains, with demonstrated technical leadership at scale.
Deep expertise in performance analysis, modeling, and hardware/software co-optimization.
Proven impact on optimizing large-scale ML workloads on modern accelerator architectures.
Strong ability to influence cross-functional teams without direct authority.
Experience contributing to industry benchmarks, open-source ecosystems, or published research is a plus.
ACADEMIC CREDENTIALS:
LOCATION:
San Jose, CA or Bellevue, WA preferred. May consider other US locations where AMD offices are based.
#LI-MV1
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.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.
This posting is for an existing vacancy.
We are seeking an exceptional Senior Fellow in Engineering to serve as a technical leader for Machine Learning workload performance and optimization across frameworks and model architectures. This is a highly visible individual contributor (IC) role with broad technical scope and company-wide impact, operating at a level equivalent to Senior Director while focusing primarily on deep technical leadership rather than organizational management.
As Senior Fellow of ML workload performance, you will define and drive the technical vision for performance optimization across multiple generations of AMD GPUs, spanning a wide range of models including state-of-the-art AI systems. You will lead through influence, setting direction for optimization strategies, guiding architectural decisions, and accelerating support for emerging models.
You will work closely with customers, business units, and engineering teams to develop performance projections, conduct deep analysis, and deliver innovative solutions that meet partner needs. You will also play a key role in industry-standard benchmarks and external technical engagements.
This role is ideal for a hands-on technical leader who is passionate about extracting maximum performance from hardware and shaping the future of AI acceleration.
The ideal candidate is a recognized technical expert with a strong track record of driving large-scale performance optimization initiatives in ML systems. You bring deep expertise in ML hardware architecture, software optimization, and performance modeling, along with a strong understanding of how model architectures map to low-level software and hardware execution.
You are comfortable operating across the full stack—from model design to kernel-level optimization—and understand the performance implications at each layer. You influence without authority, mentor senior engineers, and provide technical direction across multiple teams.
Strong knowledge of modern generative model architectures, including state-of-the-art LLMs, diffusion models, and multimodal systems, as well as distributed inference and large-scale deployment, is essential.
KEY RESPONSIBILITIES:
Define and drive the technical strategy and roadmap for ML model optimization across AMD platforms.
Serve as the highest-level technical authority in performance optimization, guiding architecture, and implementation decisions.
Lead performance tuning, profiling, and analysis of large-scale models (LLMs, diffusion, multimodal, RecSys, generative AI) across single-node and distributed environments. · Drive hardware-software co-design initiatives to influence future GPU architectures and system-level optimizations.
Collaborate across engineering, research, and customer-facing teams to deliver best-in-class performance.
Develop advanced methodologies, tools, and infrastructure for performance estimation, modeling, and benchmarking.
Provide technical mentorship to senior engineers and influence best practices across the organization.
Represent AMD in external technical forums, benchmarks, and customer engagements. · Communicate complex technical findings and recommendations to senior leadership and stakeholders.
PREFERRED EXPERIENCE:
Sr. Fellow level of experience in performance engineering, ML systems, or related domains, with demonstrated technical leadership at scale.
Deep expertise in performance analysis, modeling, and hardware/software co-optimization.
Proven impact on optimizing large-scale ML workloads on modern accelerator architectures.
Strong ability to influence cross-functional teams without direct authority.
Experience contributing to industry benchmarks, open-source ecosystems, or published research is a plus.
ACADEMIC CREDENTIALS:
LOCATION:
San Jose, CA or Bellevue, WA preferred. May consider other US locations where AMD offices are based.
#LI-MV1
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.
AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.
This posting is for an existing vacancy.
More open roles at AMD
Hiring velocity, headcount trend, and every open posting on one page.
Open postings ranked by description similarity — useful if this role isn't quite right.