AI Performance Engineer

Join Us At AMD

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.

The Role

AI Performance Engineers focus on optimizing machine learning models, profiling, bottleneck analysis, and optimal mapping to GPU. As an AI Performance Engineer, you will analyze and explore recent ML models, understand their compute and memory requirements, and optimize them on various compute hardware for both inference and training. In addition you would do profiling and analyzing various workloads on current hardware and coming up with new ways to improve their performance.

The Person

The ideal candidate will have strong experience with software optimization, GPU programming and hardware architecture. Passionate of getting the best performance out of various hardware's under different tradeoffs. If you are passionate about performance optimization, getting the best out of the HW, and shaping the future AI performance, then this role is for you.

Key Responsibilities

Benchmark, analyze, and optimize performance of key machine learning applications, on single and multi-GPU systems Design, implement, and test GPU kernels and algorithms for tensor operations like matrix multiplication and convolutions used in a variety of high-performance machine learning libraries and frameworks Deliver high-quality code and documentation following best practices for open-source software development

Preferred Experience

Understanding of GPU architectures and low-level optimization techniques, memory hierarchy, instruction scheduling, and performance tradeoffs Strong background developing applications and libraries in C++, especially high-performance computing and/or scientific software GPU software development using HIP, CUDA, or OpenCL In-depth knowledge of best-practices in software development, including testing, profiling, debugging, documentation, version control, issue tracking, and planning Experience with C++ and Python programming Experience in PyTorch, Tensorflow or MXNet Experience in high-performance computing (HPC) Strong written and spoken English language skills (our company language)

Academic Credentials

BSc, MSc, PhD or equivalent experience in Computer Science, Electrical Engineering or a related field