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At AMD, we believe technology has the power to solve the world's most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people rely on every day, innovation at AMD is shaping the future. Whether you're designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger — technology that moves the world forward. Join us and, together, we'll advance your career.
Join AMD's GPU Software team and help shape the future of machine learning and high-performance computing. As a GPU Software Architect, you will play a key role in designing, developing, and optimizing innovative GPU features that power next-generation AI and HPC workloads. Working across software, machine learning, math libraries, and GPU architecture teams, you will drive feature development from concept through deployment. Your work will span core workloads such as Convolution, GEMM, and Attention, helping deliver high-performance solutions that enable our customers to solve complex challenges at scale.
We're looking for a collaborative and curious engineer who is passionate about GPU computing, machine learning, and performance optimization. You enjoy solving complex technical problems, learning new technologies, and working with diverse teams to deliver innovative solutions. Whether your expertise comes from machine learning, HPC, GPU programming, DSP software, AI accelerators, or a combination of these areas, we encourage you to apply if you're excited about advancing high-performance compute software and helping customers achieve exceptional performance with ROCm.
KEY RESPONSIBILITIES
- Design and develop high-performance GPU kernels for machine learning and Convolution workloads using HIP.
- Collaborate with GPU architects to explore, evaluate, and leverage emerging hardware features.
- Analyse, profile, and optimize GPU kernel performance, identifying opportunities for continuous improvement.
- Create technical documentation, share best practices, and support the adoption of new capabilities within ROCm.
- Partner with engineers, researchers, customers, and ecosystem partners to enhance ROCm applications, libraries, tools, and hardware.
PREFERRED QUALIFICATIONS
- Experience with GPU, DSP, AI accelerator, or other parallel compute architectures, performance analysis, algorithm development, and machine learning workloads.
- Hands-on experience developing and optimizing GPU software using HIP, CUDA, or similar technologies.
- Understanding of GPU runtimes, compilers, machine learning frameworks, HPC libraries, and performance optimization techniques.
- Knowledge of software engineering best practices, including testing, profiling, debugging, version control, and documentation.
- Strong communication and collaboration skills, with the ability to work effectively across multidisciplinary teams.
EDUCATION & EXPERIENCE
- Bachelor's degree in computer science, Computer Engineering, or a related technical field.
- Significant experience in GPU software development, machine learning, HPC, or a related domain.