Opensource AI workload Software Engineer 

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:  AMD is looking for an influential engineer to optimize AI workload running on AMD GPUs. You will be a founding member of a core team of exceptionally talented industry specialists to define the future of AI computing solutions.  THE PERSON:  Ideal candidates should possess a "Just-Do-It" mindset and strong motivation. They must be driven to understand the status quo and explore better solutions using the first principles of thinking. Hands-on experience with state-of-the-art LLM inference and training at both the framework and kernel levels is highly preferred.   KEY RESPONSIBILITIES: Improve AMD GPU performance on open-source repositories for LLM workloads such as vLLM and SGLang. Co-optimize AI workloads on current AMD GPUs by analyzing the bottlenecks and mitigating them at the kernel level. Integrate AMD software stacks (RoCm, ATen) into open-source frameworks such as Pytorch, JAX, and Triton. Build strong technical relationships with peers and partners, and report learnings and gaps to GPU software and hardware engineers. PREFERRED EXPERIENCE: Deep AI infrastructure experience with open-source frameworks (e.g., SGLang, vLLM, Jax, XLA, Pytorch, Triton). Strong kernel optimization skills using DSLs and HIP (or CUDA), plus PTX/SASS equivalents. Hands-on knowledge of modern GPU architecture. Demonstrated open-source contributions on GitHub. Motivational leadership and excellent interpersonal skills. ACADEMIC CREDENTIALS Bachelor's, Master's, or Ph.D. in Computer Engineering, Computer Science, Electrical Engineering, or a related technical field #LI-EV1 #LI-HYBRID 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.

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.

THE ROLE:  AMD is looking for an influential engineer to optimize AI workload running on AMD GPUs. You will be a founding member of a core team of exceptionally talented industry specialists to define the future of AI computing solutions.  THE PERSON:  Ideal candidates should possess a "Just-Do-It" mindset and strong motivation. They must be driven to understand the status quo and explore better solutions using the first principles of thinking. Hands-on experience with state-of-the-art LLM inference and training at both the framework and kernel levels is highly preferred.   KEY RESPONSIBILITIES: Improve AMD GPU performance on open-source repositories for LLM workloads such as vLLM and SGLang. Co-optimize AI workloads on current AMD GPUs by analyzing the bottlenecks and mitigating them at the kernel level. Integrate AMD software stacks (RoCm, ATen) into open-source frameworks such as Pytorch, JAX, and Triton. Build strong technical relationships with peers and partners, and report learnings and gaps to GPU software and hardware engineers. PREFERRED EXPERIENCE: Deep AI infrastructure experience with open-source frameworks (e.g., SGLang, vLLM, Jax, XLA, Pytorch, Triton). Strong kernel optimization skills using DSLs and HIP (or CUDA), plus PTX/SASS equivalents. Hands-on knowledge of modern GPU architecture. Demonstrated open-source contributions on GitHub. Motivational leadership and excellent interpersonal skills. ACADEMIC CREDENTIALS Bachelor's, Master's, or Ph.D. in Computer Engineering, Computer Science, Electrical Engineering, or a related technical field #LI-EV1 #LI-HYBRID