# GPU Kernel Development Software Engineer Source: https://realanalystjobs.com/job/gpu-kernel-development-software-engineer-amd-06657d71 GPU Kernel Development Software Engineer at AMD, based in Shanghai, China. Posted on 30 October 2026, read from AMD's own careers page (Jibe), which RealAnalystJobs re-checks daily and removes the role when it closes. Updated 15 November 2026. ## Key facts - Company: [AMD](https://realanalystjobs.com/companies/amd) - Location: Shanghai, China - Posted: Oct 30, 2026 - Employment type: Full time - Source: AMD's careers page (Jibe), re-checked daily Skills: [Python](https://realanalystjobs.com/skills/python) ## Visa sponsorship The posting does not say. AMD had H-1B petitions approved for 568 workers in fiscal year 2026 (USCIS). That is history, not a promise for this role. [See the record](https://realanalystjobs.com/companies/amd#h1b-record) ## About this role ADVANCE YOUR CAREER. ADVANCE THE WORLD. 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. 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: • Deep Learning & LLM Framework Optimization: Optimize major DL/LLM frameworks (TensorFlow, PyTorch , vLLM , SGLang ) for AMD GPUs and contribute improvements upstream. • GPU Kernel & Operator Optimization: Develop and tune GPU kernels and performance-critical operators to maximize throughput and minimize latency. • Model & Architecture Optimization: Adapt and optimize LLM architectures (e.g., Llama, Qwen, DeepSeek) and apply advanced techniques like FlashAttention , PagedAttention , and quantization. • End-to-End Performance Engineering: Perform comprehensive profiling to identify bottlenecks and implement system, memory, and communication optimizations across multi-GPU and multi-node setups. • Compiler & Pipeline Acceleration: Leverage advanced compiler technologies and graph compilers to enhance the full deep learning and inference pipeline. • Research & Advanced Techniques: Prototype and integrate emerging optimization methods such as speculative decoding and weight-only quantization into production systems. • Cross-Team & Open-Source Collaboration: Collaborate with internal GPU library teams and open-source maintainers to align improvements and ensure seamless upstream integration. • Software Engineering Excellence: Apply robust engineering practices to deliver maintainable, reliable, and production-quality performance optimizations. MANDATORY EXPERIENCE: • Inference Frameworks, Model Architectures & Optimization Expertise: Deep practical experience with vLLM or SGLang , mastery of modern LLMs (e.g., DeepSeek, Qwen), strong theoretical grounding in Transformer/Attention/ MoE /KV Cache, and hands-on application of advanced inference optimizations such as FlashAttention , PagedAttention , continuous batching, and quantization (INT8/INT4/GPTQ/AWQ). • End-to-End LLM Performance Engineering: Demonstrated ability to profile, diagnose, and optimize compute , memory, and communication bottlenecks across multi-GPU and multi-node environments. • High-Performance Computing: Experience running and optimizing large-scale workloads on heterogeneous clusters with a focus on efficiency, reliability, and scalability. • Deep Learning Framework Integration: Proven ability to integrate optimized GPU kernels into TensorFlow/ PyTorch to accelerate large-scale training and inference with strong scaling and throughput. • Software Engineering Excellence & Community Contribution: Strong Python/C++ coding skills, effective debugging and testing practices, proven ability to deliver maintainable performance-critical software, and a track record of open-source contributions with strong self-motivation. • GPU Kernel Development & Optimization is a plus: Hands-on experience designing and tuning high-performance GPU kernels for AMD GPUs using HIP, CUDA, ASM, and tools like CK, CUTLASS, and Triton, with strong knowledge of GCN/RDNA architectures. • Compiler & System-Level Optimization is a plus: Foundational knowledge of LLVM, ROCm , and compiler-driven techniques for improving kernel and system performance. ACADEMIC & PREFERRED QUALIFICATIONS: • Bachelor’s and/or Master’s Degree in Computer Science , Computer Engineering, Electrical Engineering, or a related field . • Low-Level Development Skills: Experience with CUDA C++ programming for writing and debugging high-performance GPU kernels; or practical experience using Triton to develop and optimize deep learning operators. • Compiler Knowledge: Understanding or practical experience with compiler technologies like TVM or MLIR is a significant advantage. • Distributed Systems Experience: Hands-on experience with distributed inference for large-scale models (e.g., Tensor Parallel, Pipeline Parallel). \#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 stage Description from AMD's public careers feed, reproduced so you can read the role here. Apply on the company's own site; Real Analyst Jobs never submits anything for you. ## How to apply Open [this role on Real Analyst Jobs](https://realanalystjobs.com/job/gpu-kernel-development-software-engineer-amd-06657d71) and use Apply now there to reach the employer's application. The listing is re-checked against AMD's careers page daily and removed when it closes. ## AMD 20 open analyst roles on Real Analyst Jobs. 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