WHAT YOU DO AT AMD CHANGES EVERYTHING

At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond.

Together, we advance your career.

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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.

THE PERSON:

The ideal candidate has strong technical and analytical skills in high performance C++. Able to communicate effectively and work optimally with different teams across AMD. Experience in tensor libraries or machine learning execution engines is a plus.  

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

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

ACADEMIC CREDENTIALS:

• Master’s or PhD in Computer Science, Computer Engineering or related fields