162 applicants
AMD · 2 days ago
AI Performance Analyst
Santa Clara, CA
Full-time
Hybrid
Senior Level
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Hiring Manager
ELIA VALLADARES
Insider Connection @AMD
Responsibilities
Strong understanding of datacenter GPU microarchitectures
Assess scalability and efficiency of AI models and algorithms based on best-known architecture
Partner with performance architects to drive performance studies for AMD Instinct GPU architectures
Analyze performance projections and document the value proposition of AMD Instinct GPUs
Engage with software, hardware, and performance teams to identify optimization opportunities
Present technical projections to various audiences
Apply benchmarking methodologies, performance analysis, workload profiling, and debugging tools
Communicate findings to engineering and leadership teams
Collaborate and work as a team player
Qualification
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Required
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.
Computer Science or Computer Engineering degree required.
Preferred
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.
Benefits
Employee Stock Purchase Plan
Competitive benefits
Company
AMD
Advanced Micro Devices (AMD) is a semiconductor company that designs and develops graphics units, processors, and media solutions.
Founded in 1969
10,001+ employees
H1B Sponsorship
AMD has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Trends of Total Sponsorships
2023 (465)
2022 (689)
2021 (578)
2020 (559)
Funding
Current Stage
Public CompanyTotal Funding
unknownKey Investors
Daniel Loeb
2023-03-02Post Ipo Equity· Undisclosed
2021-06-29Post Ipo Equity· Undisclosed
2009-01-20Acquired· by Qualcomm ($65M)
Leadership Team
Mark Papermaster
CTO and EVP
Raghunath Nambiar
Corporate Vice President and Chief Technology Officer
Recent News
2024-06-05
2024-06-05
Company data provided by crunchbase
