WHAT YOU DO AT AMD CHANGES EVERYTHINGWe care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences - the building blocks for the data center, artificial intelligence, PCs, gaming and embedded.

Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world's most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives.

AMD together we advance_THE ROLE: In this role, you will join the organization to enable AI acceleration at scale. You will work on developing tools and methodologies to optimize and realize full system performance for AI workloads on Ryzen AI SoC. You will explore novel optimization techniques to accelerate the latest AI models addressing vision, language, and generative models, working with the leading engineers in AMD's CPU, GPU, and Adaptable Compute teams.

You will be tasked with analyzing AI workloads, analyzing system-level performance bottlenecks, and finding ways to achieve the best performance and power. KEY RESPONSIBILITIES: Develop tools to analyze AI workloads and find optimal mapping to AI accelerators. Work with cross-functional teams to optimize various parts of the SW stack - AI Compiler, AI frameworks, device drivers, and firmware.

Explore and iterate on finding optimal tiling and data movement strategies for the latest AI models, including generative AI and new models. Work with teams across AMD to specify requirements for backend libraries, compilers, and toolchains to accelerate AI models on AMD platforms. PREFERRED EXPERIENCE: Solid knowledge of AI and ML concepts and techniques.

Practical experience applying these concepts to solve real-world problems in the context of research or work experience. Understanding the performance implications on AI acceleration of different compute, memory, and communication configurations and hardware and software implementation choices. Developing and optimizing code for VLIW processors.

Analyzing code for high performance CONV, GEMM and non-linear operators - focusing on compute and data movement Deep understanding of AI frameworks, preferably ONNX. Experience with AI/ML inference stacks such as ONNXRuntime. Previous experience with GPU acceleration with either AMD or Nvidia GPUs.

Working collaboratively through version control systems (eg, git) Experience in benchmarking methodologies and debugging tools. Effective communication and problem-solving skills.ACADEMIC CREDENTIALS: Master's degree in computer science, Computer Engineering, Electrical Engineering, or equivalent.

PhD in one of these fields preferred.LOCATION:San Jose, CA.AMD, your base pay is one part of your total rewards package. Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position.

You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employees have the opportunity to own shares of AMD stock, as well as a discount when purchasing AMD stock if voluntarily participating in AMD's Employee Stock Purchase Plan. You'll also be eligible for competitive benefits described in more detailhere.

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.

Job type: FULL TIMECategories: Engineering.