Senior GPU Kernel Optimizer for AI & LLM

Advanced Micro Devices, Inc.; San Jose (CA); Ibrido; USD 180.000 - 240.000; Tempo pieno

Descrizione del lavoro

Advanced Micro Devices, Inc. (AMD) in San Jose seeks a senior technical member to design, develop, and optimize high-performance GPU kernels for LLMs and ML models, analyzing bottlenecks and driving architecture-aware optimizations across platforms.

You will collaborate with GPU architecture, compiler, library, and framework teams to deliver scalable solutions and advance GPU performance, with leadership guiding projects independently within a high-performing team.

Competenze

• Bachelors or Masters degree in computer engineering, computer science or a related field.

Mansioni

• Architect and Optimize AI Workloads: Lead the optimization of LLMs, quantized models, and emerging AI workloads for AMD GPU architectures.
• Develop High-Performance GPU Kernels: Design, implement, profile, and optimize GPU kernels, with a strong focus on maximizing hardware utilization and application performance.
• Drive Performance Analysis: Perform deep performance characterization across compute, memory bandwidth, cache hierarchy, synchronization, kernel scheduling, and execution efficiency to identify and eliminate bottlenecks.
• Advance Compiler and Code-Generation Technologies: Develop compiler-level optimizations and code-generation techniques using LLVM, MLIR, and related technologies to achieve portable and scalable GPU performance.
• Innovate with AI-Assisted Development: Build AI-powered coding agents and automation workflows for kernel generation, optimization, benchmarking, and validation.
• Collaborate with model and infrastructure teams to improve end-to-end AI system performance.

Conoscenze

C++

Python

GPU compute

CUDA/HIP

Performance analysis

Self-starter

Formazione

Bachelor's or Master's in computer engineering or computer science

Descrizione del lavoro

Advanced Micro Devices, Inc. (AMD) in San Jose seeks a senior technical member to design, develop, and optimize high-performance GPU kernels for LLMs and ML models, analyzing bottlenecks and driving architecture-aware optimizations across platforms.

You will collaborate with GPU architecture, compiler, library, and framework teams to deliver scalable solutions and advance GPU performance, with leadership guiding projects independently within a high-performing team.