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Advanced Microdevices Pvt. Ltd. (India) · 1 month ago

Software Development Engineer - Kernel Development

Santa Clara, CA

Full-time

Onsite

Senior Level

Advanced Micro Devices, Inc is committed to building innovative products that enhance next-generation computing experiences. The role involves optimizing and developing deep learning frameworks for AMD GPUs, focusing on enhancing GPU kernels and improving inference performance across multi-GPU and multi-node systems.

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Responsibilities

Optimize Deep Learning Frameworks: Enhance and optimize frameworks like PyTorch / vllm / SGLang for AMD GPUs in open-source repositories

Design and scale: multi‑GPU inference strategies (TP/PP/EP hybrid)

Develop & Optimize Models: Design and optimize deep learning models specifically for AMD GPU performance

Collaborate with GPU Library Teams: Work closely with internal teams to analyze and improve training and inference performance on AMD GPUs

Collaborate with Open-Source Maintainers: Engage with framework maintainers to ensure code changes are aligned with requirements and integrated upstream

Work in Distributed Computing Environments: Optimize deep learning performance on both scale-up (multi-GPU) and scale-out (multi-node) systems

Utilize Cutting-Edge Compiler Tech: Leverage advanced compiler technologies to improve deep learning performance

Optimize Deep Learning Pipeline: Enhance the full pipeline, including integrating graph compilers

Software Engineering Best Practices: Apply sound engineering principles to ensure robust, maintainable solutions

Qualification

PythonC++Deep LearningGPU Kernel DevelopmentDistributed ComputingCompiler OptimizationOpen-Source ContributionSoftware Engineering Best PracticesAnalytical SkillsProblem-Solving

Required

Strong technical and analytical expertise in Python development within Linux environments

Ability to define goals, manage development efforts, and deliver high-quality solutions

Strong problem-solving skills

Proactive approach

Keen understanding of software engineering best practices

Experience optimizing and developing deep learning frameworks for AMD GPUs

Experience enhancing GPU kernels, deep learning models, and finetuning inference performance across multi-GPU and multi-node systems

Experience engaging with internal framework teams and open-source maintainers

Experience utilizing cutting-edge technologies and advanced engineering principles to drive continuous improvement

Preferred

Strong background in GPU kernel development and LLM inference frameworks

Hands-on understanding of SGLang internals or similar stacks such as vLLM and FasterTransformer

Solid experience with distributed inference scaling and proven contributor to upstream open-source projects

Strong and significant experience in integrating optimized GPU performance into machine learning frameworks (e.g., TensorFlow, PyTorch) to accelerate model training and inference, with a focus on scaling and throughput

Expert in Python and C++, with experience in debugging, performance tuning, and test design to ensure high-quality, maintainable software solutions

Solid experience in running large-scale workloads on heterogeneous compute clusters, optimizing for efficiency and scalability

Foundational understanding of compiler theory and tools like LLVM and ROCm for kernel and system performance optimization

Master's or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related field