AI Software System Designer

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 an AICE Software System Design Engineer, you will be responsible for the development, debugging, optimization, and technical support of machine learning E2E custom software solutions for AMD server GPUs.   THE PERSON: Success in this role requires expert knowledge in machine learning areas such as kernel operators (like MHA, MLA, MOE etc.) by program languages (like Triton/DSL, cuda/hip, PTX/ASM etc.) and some development libraries (like cutlass/CK etc.), frameworks, distributions, compilers, performance optimizations for inference or training, along with strong programming skills in C++ and Python. Candidates must also have hands-on experience with industry AI use scenarios and solutions, end-to-end pipelines, frameworks or SDKs, parallel programming, and hanving strong debugging and development skillsets.   KEY RESPONSIBILITIES: Position technical proposals and support to top customers. Provide significant contribution to customer PoC success. Drive custom requirements for AI SW performance and stability, including from POC requirement to POR release, from GPU kernel to frameworks and distribution solutions. Collaborate and interact with different teams to analyze and optimize training and inference workloads from kernels, frameworks to solutions Analyze competitive solutions to identify strength and weakness for articulate value propositions. Apply your knowledge of software engineering best practices    PREFERRED EXPERIENCE:  Ability to work independently, define project goals and scope, and lead your own development effort.  Solid communication skills, in both English and mandarin.  Excellent in GPU kernel primitive like Attention (FA, PA, MLA, linear Attn etc.), MOE, TOPK design (algorithms) and development (with Triton/DSL, Cutlass/CK, CUDA/HIP, PTX/ASM etc.). Excellent programming skills in Python, C++ and software skills, including debugging and performance analysis.  Experiences with model inference optimization process like GEMM/convolution tuning, graph optimization and operator fusion. Experiences with AI frameworks(e.g. vLLM, Sglang, Megatron-LM, Deepspeed, TensorRT, TensorRT-LLM etc.). Knowledge of compiler (Torch, Triton, LLVM, XLA HLO, graph) is a plus. Knowledge of Linux ROCm/CUDA runtime and KMD/UMD driver is a plus. Knowledge of AI distribution solutions (i.e. EP/SP/CP/TP/PP/DP, DeepEp, DualPipe, PD aggregation etc., KV cache transfer and storage). Knowledge of AI distributed network communication with multi-GPU and multi-node collective communication primitives (NCCL/RCCL), NIC/GPU drivers for RDMA/GDR and high-speed network etc. Knowledge of Linux OS/driver, CI and toolchain (profiler/DCGM) development and debugging.   ACADEMIC CREDENTIALS:  Bachelor’s or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent  #LI-FL1 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.

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.

THE ROLE: As an AICE Software System Design Engineer, you will be responsible for the development, debugging, optimization, and technical support of machine learning E2E custom software solutions for AMD server GPUs.   THE PERSON: Success in this role requires expert knowledge in machine learning areas such as kernel operators (like MHA, MLA, MOE etc.) by program languages (like Triton/DSL, cuda/hip, PTX/ASM etc.) and some development libraries (like cutlass/CK etc.), frameworks, distributions, compilers, performance optimizations for inference or training, along with strong programming skills in C++ and Python. Candidates must also have hands-on experience with industry AI use scenarios and solutions, end-to-end pipelines, frameworks or SDKs, parallel programming, and hanving strong debugging and development skillsets.   KEY RESPONSIBILITIES: Position technical proposals and support to top customers. Provide significant contribution to customer PoC success. Drive custom requirements for AI SW performance and stability, including from POC requirement to POR release, from GPU kernel to frameworks and distribution solutions. Collaborate and interact with different teams to analyze and optimize training and inference workloads from kernels, frameworks to solutions Analyze competitive solutions to identify strength and weakness for articulate value propositions. Apply your knowledge of software engineering best practices    PREFERRED EXPERIENCE:  Ability to work independently, define project goals and scope, and lead your own development effort.  Solid communication skills, in both English and mandarin.  Excellent in GPU kernel primitive like Attention (FA, PA, MLA, linear Attn etc.), MOE, TOPK design (algorithms) and development (with Triton/DSL, Cutlass/CK, CUDA/HIP, PTX/ASM etc.). Excellent programming skills in Python, C++ and software skills, including debugging and performance analysis.  Experiences with model inference optimization process like GEMM/convolution tuning, graph optimization and operator fusion. Experiences with AI frameworks(e.g. vLLM, Sglang, Megatron-LM, Deepspeed, TensorRT, TensorRT-LLM etc.). Knowledge of compiler (Torch, Triton, LLVM, XLA HLO, graph) is a plus. Knowledge of Linux ROCm/CUDA runtime and KMD/UMD driver is a plus. Knowledge of AI distribution solutions (i.e. EP/SP/CP/TP/PP/DP, DeepEp, DualPipe, PD aggregation etc., KV cache transfer and storage). Knowledge of AI distributed network communication with multi-GPU and multi-node collective communication primitives (NCCL/RCCL), NIC/GPU drivers for RDMA/GDR and high-speed network etc. Knowledge of Linux OS/driver, CI and toolchain (profiler/DCGM) development and debugging.   ACADEMIC CREDENTIALS:  Bachelor’s or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent  #LI-FL1