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职位AMD

Principal Modeling Architect - DC GPU

AMD

Principal Modeling Architect - DC GPU

AMD

San Jose, California

·

On-site

·

Full-time

·

3d ago

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 AI and HPC landscape. Our mission is to design and market exceptional products—anchored by our Instinct™ GPU portfolio—that power the next generation of computing in enterprise data centers, cloud, and supercomputing environments. If you’re excited by AI disruption and want to be part of building something big, join us.

THE ROLE

AMD is seeking a highly accomplished Principal Modeling Architect to join the Product Architecture and Workload Strategy team for Data Center GPU. This role will be responsible for leading the development and application of advanced workload modeling methodologies to inform the architecture, design, and optimization of AMD’s next-generation Instinct™ GPU and data center platforms.

You will drive deep analysis of emerging AI/ML, HPC, and data analytics workloads, translating insights into actionable architectural requirements and performance projections. Your work will directly influence silicon, system, and software design, ensuring AMD platforms are optimized for current and future workload trends.

KEY REPSONSIBILITIESWorkload Modeling Leadership

  • Develop and refine workload modeling frameworks to characterize and project performance, scalability, and resource utilization for AI/ML, HPC, and data analytics workloads.
  • Analyze emerging model architectures (e.g., LLMs, transformer variants, graph neural networks), datatypes, and scaling methodologies to anticipate future platform requirements.
  • Collaborate with architecture, silicon design, software, and performance engineering teams to translate workload insights into platform-level technical requirements.
  • Lead benchmarking, profiling, and simulation efforts to validate architectural assumptions and guide design trade-offs.
  • Produce detailed workload characterization reports, performance projections, and sensitivity analyses to inform platform strategy and technical decision-making.

REQUIRED QUALIFICATIONS

  • 12+ years of experience in workload modeling, performance engineering, system architecture, or related technical domains.
  • Demonstrated expertise in modeling and analyzing AI/ML, HPC, or large-scale data analytics workloads on GPU or accelerator platforms.
  • Deep understanding of performance modeling methodologies, benchmarking tools, simulation environments, and workload characterization techniques.
  • Experience collaborating across hardware, software, and system engineering teams to drive workload-informed architectural decisions.
  • Strong analytical, communication, and technical writing skills; ability to synthesize complex data into actionable insights.
  • Advanced degree in Computer Science, Electrical Engineering, or related field preferred.

PREFERRED QUALIFICATIONS

  • Experience with ROCm, CUDA, or other GPU programming frameworks.
  • Familiarity with compiler/runtime systems, kernel libraries, and developer tooling for AI/ML workloads.
  • Track record of publishing workload analysis or performance modeling research in peer-reviewed venues.
  • Experience engaging with hyperscalers, CSPs, or large enterprise customers on workload deployment and optimization.

This role is not eligible for visa sponsorship.LOCATION:

Bay Area or Remote:

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.

THE TEAM

AMD's Data Center GPU organization is transforming the AI and HPC landscape. Our mission is to design and market exceptional products—anchored by our Instinct™ GPU portfolio—that power the next generation of computing in enterprise data centers, cloud, and supercomputing environments. If you’re excited by AI disruption and want to be part of building something big, join us.

THE ROLE

AMD is seeking a highly accomplished Principal Modeling Architect to join the Product Architecture and Workload Strategy team for Data Center GPU. This role will be responsible for leading the development and application of advanced workload modeling methodologies to inform the architecture, design, and optimization of AMD’s next-generation Instinct™ GPU and data center platforms.

You will drive deep analysis of emerging AI/ML, HPC, and data analytics workloads, translating insights into actionable architectural requirements and performance projections. Your work will directly influence silicon, system, and software design, ensuring AMD platforms are optimized for current and future workload trends.

KEY REPSONSIBILITIESWorkload Modeling Leadership

  • Develop and refine workload modeling frameworks to characterize and project performance, scalability, and resource utilization for AI/ML, HPC, and data analytics workloads.
  • Analyze emerging model architectures (e.g., LLMs, transformer variants, graph neural networks), datatypes, and scaling methodologies to anticipate future platform requirements.
  • Collaborate with architecture, silicon design, software, and performance engineering teams to translate workload insights into platform-level technical requirements.
  • Lead benchmarking, profiling, and simulation efforts to validate architectural assumptions and guide design trade-offs.
  • Produce detailed workload characterization reports, performance projections, and sensitivity analyses to inform platform strategy and technical decision-making.

REQUIRED QUALIFICATIONS

  • 12+ years of experience in workload modeling, performance engineering, system architecture, or related technical domains.
  • Demonstrated expertise in modeling and analyzing AI/ML, HPC, or large-scale data analytics workloads on GPU or accelerator platforms.
  • Deep understanding of performance modeling methodologies, benchmarking tools, simulation environments, and workload characterization techniques.
  • Experience collaborating across hardware, software, and system engineering teams to drive workload-informed architectural decisions.
  • Strong analytical, communication, and technical writing skills; ability to synthesize complex data into actionable insights.
  • Advanced degree in Computer Science, Electrical Engineering, or related field preferred.

PREFERRED QUALIFICATIONS

  • Experience with ROCm, CUDA, or other GPU programming frameworks.
  • Familiarity with compiler/runtime systems, kernel libraries, and developer tooling for AI/ML workloads.
  • Track record of publishing workload analysis or performance modeling research in peer-reviewed venues.
  • Experience engaging with hyperscalers, CSPs, or large enterprise customers on workload deployment and optimization.

This role is not eligible for visa sponsorship.LOCATION:

Bay Area or Remote:

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.

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关于AMD

AMD

AMD

Public

Advanced Micro Devices, Inc. (AMD) is an American multinational semiconductor company headquartered in Santa Clara, California.

10,001+

员工数

Santa Clara

总部位置

$240B

企业估值

评价

3.7

10条评价

工作生活平衡

2.8

薪酬

3.2

企业文化

4.1

职业发展

3.4

管理层

3.8

68%

推荐给朋友

优点

Great team culture and spirit

Innovative projects and cutting-edge technology

Supportive management and leadership

缺点

High workload and overwhelming demands

Work-life balance challenges

High pressure and stressful deadlines

薪资范围

6个数据点

L2

L3

L4

L5

L6

L2 · Data Analyst L2

0份报告

$76,430

年薪总额

基本工资

$30,572

股票

$38,215

奖金

$7,643

$53,501

$99,359

面试经验

2次面试

难度

3.0

/ 5

时长

14-28周

录用率

50%

面试流程

1

Application Review

2

Recruiter Screen

3

Hiring Manager Interview

4

Technical Interview

5

Offer

常见问题

Technical Knowledge

Behavioral/STAR

Past Experience

Problem Solving