Software Development Engineer – GPU Kernel & Community Development

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:     As a core member of the team, you will play a pivotal role in  optimizing  and developing deep learning frameworks for AMD GPUs. Your experience will be critical in enhancing GPU kernels, deep learning models, and training/inference performance across multi-GPU and multi-node systems. You will engage with both internal GPU library teams and open-source maintainers to ensure seamless integration of optimizations,  utilizing   cutting-edge  compiler technologies and advanced engineering principles to drive continuous improvement.     THE PERSON:     Skilled engineer with strong technical and analytical  expertise  in C++ development within Linux environments. The ideal candidate will thrive in both collaborative team settings and independent work, with the ability to define goals, manage development efforts, and deliver high-quality solutions. Strong problem-solving skills, a proactive approach, and a keen understanding of software engineering best practices are essential.       KEY RESPONSIBILITIES:     Optimize  Deep Learning Frameworks:  Enhance and  optimize  frameworks like TensorFlow and  PyTorch  for AMD GPUs in open-source repositories.   Develop GPU Kernels:  Create and  optimize  GPU kernels to maximize performance for specific AI operations.   Develop & Optimize Models:  Design and  optimize  deep learning models specifically for AMD GPU performance.   Collaborate with GPU Library Teams:  Work closely with internal teams to analyze and improve training and inference performance on AMD GPUs.   Collaborate with Open-Source Maintainers:  Engage with framework maintainers to ensure code changes are aligned with requirements and integrated upstream.   Work in Distributed Computing Environments:   Optimize  deep learning performance on both scale-up (multi-GPU) and scale-out (multi-node) systems.   Utilize Cutting-Edge Compiler Tech:  Leverage advanced compiler technologies to improve deep learning performance.   Optimize  Deep Learning Pipeline:  Enhance the full pipeline, including integrating graph compilers.   Software Engineering Best Practices:  Apply sound engineering principles to ensure robust, maintainable solutions.   Outstanding written and verbal communication : Publish tutorials, technical blogs, and keep user guides, tutorials, and API references up‑to‑date.   Passion for open‑source and AI acceleration , community‑oriented mindset.     PREFERRED EXPERIENCE:     GPU Kernel Development & Optimization:   Experienced  in designing and  optimizing  GPU kernels for deep learning on AMD GPUs using HIP, CUDA, and assembly (ASM). Strong knowledge of AMD architectures (GCN, RDNA) and low-level programming to maximize performance for AI operations,  leveraging  tools like Compute Kernel (CK), CUTLASS, and Triton for multi-GPU and multi-platform performance.   Deep Learning Integration:   E xperience d  in integrating optimized GPU performance into machine learning frameworks (e.g., Py Torch, vLLM ) to accelerate model training and inference, with a focus on scaling and throughput.   Software Engineering:   S kill ed in Python and C++, with experience in debugging, performance tuning, and test design to ensure high-quality, maintainable software solutions. Hands‑on experience with modern inference engines such as vLLM, SGLang, or other large‑scale or multi‑modal inference runtimes.  Written and Verbal Communication:  Outstanding communication skills and  e xperienced  in publishing technical tutorials and blogs,  maintaining  comprehensive and up-to-date user documentation, including user guides, tutorials, and API references.   Open-Source and AI Acceleration:   Passionate and a c tive contributor to open-source initiatives with a strong interest in AI acceleration technologies. Values community collaboration and  knowledge   sharing to  drive innovation and accessibility in AI development.     ACADEMIC CREDENTIALS:     Bachelor ’ s and/or  Master’s  Degree   in Computer Science , Computer Engineering, Electrical Engineering, or  a related field .     #LI-JG1 Benefits offered are described:  AMD benefits at a glance.   AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law.   We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.   AMD may use Artificial Intelligence to help screen, assess or select applicants for this position.  AMD’s “Responsible AI Policy” is available here.   This posting is for an existing vacancy.