AI Framework Engineer

Job description

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

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: Strong 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

Expert e xperience 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

Expert in 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 solid 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

Expert 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).

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.