Sr. Software Development Engineer

at  Advanced Micro Devices Inc

PREFERRED EXPERIENCE:

• Ability to work independently, define project goals and scope, and lead your own development effort
• Deep Learning experience or knowledge - Natural Language Processing, Vision, Audio, Recommendation systems
• Programming in High-Performance Domain-Specific Languages for GPU or ML ASIC Computing (HIP, CUDA, OpenCL, Triton, KNYFE, Mojo)
• Using debuggers (LLDB, GDB) and profilers on heterogeneous hardware
• PyTorch or TensorFlow
• Familiarity with ML Graph Compilers (Glow, FX, XLA) is a plus
• Knowledge of the lower levels of typical ML workflows from MLIR to LLVM all the way down to assembly language(s) is a plus

WHAT YOU DO AT AMD CHANGES EVERYTHING

We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives.
AMD together we advance_
Responsibilities:

THE ROLE:

We are looking for an AI Software development engineer who is passionate about building and optimizing deep learning applications and machine learning frameworks.
Be a part of an AMD development team and the open-source community to design, develop, test and deploy improvements to make us the best platform for generative artificial intelligence and deep neural networks. Incredibly talented industry specialists.

KEY RESPONSIBILITIES:

• Optimize key deep learning models on AMD GPUs
• Develop and finetune inference and serving engines for large language models
• Collaborate with AMD’s architecture specialists to improve future products
• Collaborate with operator libraries team to analyze and optimize training and inference for deep learning
• Work in a distributed computing setting to optimize for both scale-up (multi-accelerator) and scale-out (multi-node) systems
• Optimize the entire deep learning pipeline including graph compiler integration
• Participate in new ASIC and hardware bring ups
• Apply your knowledge of software engineering best practices