GPU Kernel Developer - AI Models Advanced Micro Devices (AMD)

2.0 - 7.0 years

4 - 8 Lacs

Bengaluru, Karnataka, India

On-site

THE ROLE: AMD is looking for a GPU kernel development engineer who is talented in developing high performance kernels for state-of-the-art and upcoming GPU hardware . You will be a member of a core team of incredibly talented industry specialists and will work with the very latest hardware and software technology. THE PERSON: Experienced in GPU kernel development and optimization for AI/HPC applications. Strong technical and analytical skills in GPU computing, hardware architecture, and deep understanding of HIP/CUDA/OpenCL/Triton development. Ability to work as part of a team, deliver to project scope, and communicate to a technical/non-technical audience. KEY RESPONSIBILITIES: Develop high performance GPU kernels for key AI operators on AMD GPUs Optimize GPU code using structured and disciplined methodology - profiling to identify gaps, roofline-analysis on hardware, identify key set of optimizations, establish uplift and line-of-sight, prototype and develop optimizations Support mission-critical workloads in NLP/LLM, Recommendation, Vision and Audio Collaborate and interact with system level performance architects, GPU hardware specialists, power/clock tuning teams, performance validation teams, and performance marketing teams to analyze and optimize training and inference for AI Work with open-source framework maintainers to understand their requirements and have your code changes integrated upstream Debug, maintain and optimize GPU kernels, understand and drive AI operator performance (GEMM, Attention, Distributed scale-up/out communication, etc.) Apply your knowledge of software engineering best practices PREFERRED EXPERIENCE: Knowledge of GPU computing (HIP, CUDA, OpenCL, Triton) Knowledge and experience in optimizing GPU kernels Expertise in using profiling, debugging tools Core understanding of GPU hardware Excellent C/C++/Python programming and software design skills, including debugging, performance analysis, and test design. ACADEMIC CREDENTIALS: Masters or PhD or equivalent experience in Computer Science, Computer Engineering, or related field

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