Job Description: THE ROLE: THE PERSON: KEY RESPONSIBILITIES:

Optimize open-source deep learning training libraries, such as Megatron and Transformer Engine, for enhanced performance on AMD GPUs.
Analyze and optimize key deep learning models for performance on AMD GPUs in a distributed computing environment, targeting both scale-up (multi-GPU) and scale-out (multi-node) architectures.
Apply software engineering best practices while staying informed of trends and innovations in software, hardware, algorithms and architecture.
Contribute to the development and bring-up of new ASIC and hardware.
Apply a data-driven approach to optimization efforts and design groundbreaking AMD technologies.
Debug and resolve existing issues while researching more efficient alternatives to achieve the same objectives.
Collaborate with internal GPU library teams and develop technical relationships with peers and partners to optimize deep learning training.

PREFERRED EXPERIENCE:

Programming \& Development:
Expertise in C/C and Python, with strong skills in object-oriented programming, debugging, performance optimization, and concurrent programming.
Familiar with source control (GitHub), CI/CD, and Linux debugging/profiling tools.
GPU Kernel Development:
Experienced in GPU kernel optimization for deep learning using HIP and CUDA on AMD GPUs (GCN, RDNA).
Skilled in programming and performance optimization with tools like Composable Kernel (CK), CUTLASS, Triton, and assembly (ASM).
Deep Learning \& Optimization:
Expertise in integrating GPU performance into TensorFlow and PyTorch for model training and inference optimization.
Experience in analyzing and optimizing deep learning workloads with a focus on scaling and throughput.
Collaboration \& Communication:
Strong problem-solving and communication skills, with proven success in team collaboration.
Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent

Advanced Micro Devices

Advanced Micro Devices

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