AI Performance Analyst

Mar 07, 2024
Santa Clara, Cuba
... Not specified
... Intermediate
Full time
... Office work


WHAT YOU DO AT AMD CHANGES EVERYTHING

We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives. 

AMD together we advance_




THE ROLE: 

 AMD's Datacenter GPU Business Unit is seeking an AI Performance Analyst to help quantify and communicate the capabilities of our next-generation AMD Instinct accelerators. This role will partner with engineering and product marketing teams to deeply analyze AMD Instinct GPUs and how our design decisions impact real-world AI workloads at scale. The Performance Analyst will model AI workload requirements, identify optimization opportunities across hardware and software stacks, and clearly present technical findings to technical and business leadership audiences.

  

THE PERSON: 

We need someone passionate about AMD GPU architecture and excited to highlight AMD Instinct's leadership performance to shape our roadmap and drive adoption in AI, HPC, and graphics intensive workloads. The ideal candidate will have expertise in artificial intelligence, deep learning models, GPU hardware architectures, and profiling GPU performance. They should have solid knowledge of AI and machine learning concepts including deep learning, NLP, computer vision, and generative AI. Hands-on experience benchmarking, analyzing performance, debugging and optimization of hardware for AI workloads is key. Finally, strong communication skills are required to articulate technical details clearly to both engineering teams as well as executives.

 

KEY RESPONSIBILITIES: 

  • Strong understanding of datacenter GPU microarchitectures
  • Ability to assess scalability and efficiency of AI models and algorithms based on best known architecture, and speeds/feeds data.
  • Partner closely with performance architects to articulate the performance studies that need to be driven to maximize the value of AMD Instinct GPU architectures.
  • Analyze performance projections and articulate/document the value proposition of AMD Instinct GPUs - at the node, pod, and cluster level.
  • Engage the software, hardware, and performance teams to identify further optimization opportunities based on client feedback.
  • Present technical projections in digestible summaries to a range of audiences - from highly technical clients to business executives.

 

PREFERRED EXPERIENCE: 

  • Solid knowledge of Artificial Intelligence (AI) and Machine Learning (ML) concepts and techniques, including deep learning, natural language processing, generative AI, and computer vision, as well as practical experience applying these concepts to solve real-world problems through research or work experience.
  • Experience in benchmarking methodologies, performance analysis, workload profiling, performance monitoring and debugging tools.
  • Strong communication skills to articulate findings to both engineering and leadership.
  • Willingness to roll up your sleeves and do whatever is necessary to accomplish the goals.
  • Ability to see ahead comprehensively and devise a strong plan of action, and ensure execution happens on time, every time.
  • Ability to get things done and produce conclusive, measurable results within time commitments.
  • Collaborative and strong team player
  • Deep Learning Frameworks (PyTorch, TensorFlow, Jax) - Hands-on experience building, training, and optimizing deep neural networks that utilize GPUs.
  • Performance Analysis Tools - Expertise using profilers, benchmarks (MLPerf), debuggers to analyze, profile, and tune AMD systems for AI workloads.
  • Large-Scale Distributed Training - Knowledge of techniques for scaling AI model training across multi-GPU or multi-node distributed topologies leveraging accelerators.

ACADEMIC CREDENTIALS: 

  • Computer Science or Computer Engineering degree required. 

  LOCATION: 

  • Santa Clara, California

 

#LI-EV1

#LI-HYBRID 




At AMD, your base pay is one part of your total rewards package.  Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position. You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employees have the opportunity to own shares of AMD stock, as well as a discount when purchasing AMD stock if voluntarily participating in AMD’s Employee Stock Purchase Plan. You’ll also be eligible for competitive benefits described in more detail here.

 

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.

At AMD, your base pay is one part of your total rewards package.  Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position. You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employees have the opportunity to own shares of AMD stock, as well as a discount when purchasing AMD stock if voluntarily participating in AMD’s Employee Stock Purchase Plan. You’ll also be eligible for competitive benefits described in more detail here.

 

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: 

 AMD's Datacenter GPU Business Unit is seeking an AI Performance Analyst to help quantify and communicate the capabilities of our next-generation AMD Instinct accelerators. This role will partner with engineering and product marketing teams to deeply analyze AMD Instinct GPUs and how our design decisions impact real-world AI workloads at scale. The Performance Analyst will model AI workload requirements, identify optimization opportunities across hardware and software stacks, and clearly present technical findings to technical and business leadership audiences.

  

THE PERSON: 

We need someone passionate about AMD GPU architecture and excited to highlight AMD Instinct's leadership performance to shape our roadmap and drive adoption in AI, HPC, and graphics intensive workloads. The ideal candidate will have expertise in artificial intelligence, deep learning models, GPU hardware architectures, and profiling GPU performance. They should have solid knowledge of AI and machine learning concepts including deep learning, NLP, computer vision, and generative AI. Hands-on experience benchmarking, analyzing performance, debugging and optimization of hardware for AI workloads is key. Finally, strong communication skills are required to articulate technical details clearly to both engineering teams as well as executives.

 

KEY RESPONSIBILITIES: 

  • Strong understanding of datacenter GPU microarchitectures
  • Ability to assess scalability and efficiency of AI models and algorithms based on best known architecture, and speeds/feeds data.
  • Partner closely with performance architects to articulate the performance studies that need to be driven to maximize the value of AMD Instinct GPU architectures.
  • Analyze performance projections and articulate/document the value proposition of AMD Instinct GPUs - at the node, pod, and cluster level.
  • Engage the software, hardware, and performance teams to identify further optimization opportunities based on client feedback.
  • Present technical projections in digestible summaries to a range of audiences - from highly technical clients to business executives.

 

PREFERRED EXPERIENCE: 

  • Solid knowledge of Artificial Intelligence (AI) and Machine Learning (ML) concepts and techniques, including deep learning, natural language processing, generative AI, and computer vision, as well as practical experience applying these concepts to solve real-world problems through research or work experience.
  • Experience in benchmarking methodologies, performance analysis, workload profiling, performance monitoring and debugging tools.
  • Strong communication skills to articulate findings to both engineering and leadership.
  • Willingness to roll up your sleeves and do whatever is necessary to accomplish the goals.
  • Ability to see ahead comprehensively and devise a strong plan of action, and ensure execution happens on time, every time.
  • Ability to get things done and produce conclusive, measurable results within time commitments.
  • Collaborative and strong team player
  • Deep Learning Frameworks (PyTorch, TensorFlow, Jax) - Hands-on experience building, training, and optimizing deep neural networks that utilize GPUs.
  • Performance Analysis Tools - Expertise using profilers, benchmarks (MLPerf), debuggers to analyze, profile, and tune AMD systems for AI workloads.
  • Large-Scale Distributed Training - Knowledge of techniques for scaling AI model training across multi-GPU or multi-node distributed topologies leveraging accelerators.

ACADEMIC CREDENTIALS: 

  • Computer Science or Computer Engineering degree required. 

  LOCATION: 

  • Santa Clara, California

 

#LI-EV1

#LI-HYBRID 

COMPANY JOBS
1739 available jobs
WEBSITE