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.

AMD is looking for an influential software engineer who is passionate about improving the performance of key applications and benchmarks. You will be a member of a core team of incredibly talented industry specialists and will work with the very latest hardware and software technology.

As a Staff Software Developer, you will be at the heart of AMD's AI strategy, tackling one of the most exciting challenges in the industry: training and running AI to make AI itself more efficient on GPUs on the fly, which can dramatically alter the trajectory of AI progress. This is a high-impact, hands-on role where your work will directly define the software that powers the future of AI.

Architect and Drive the AI Software Stack: You will establish best practices and optimize performance from the lowest-level GPU kernels to large-scale distributed systems, shaping the foundational software for AMD hardware. By leveraging cutting-edge Large Language Models (LLMs) and agent-based technologies, you will accelerate the development and performance enhancement of the AMD ROCm ecosystem, ensuring it remains at the forefront of AI innovation.

Accelerate Foundational Models: Your work will directly accelerate cutting-edge applications like foundation models (LLMs) and autonomous AI agents, ensuring AMD is the platform of choice for the most demanding workloads.

Innovate Across Hardware and Software: You will contribute to the entire co-design lifecycle, from influencing future GPU architectures to developing groundbreaking software for new accelerators and collaborating with the broader AI community.

Success in this role requires a deep passion for software engineering, strong technical ownership to see complex problems through to resolution, and the ability to influence technical direction across teams. As a senior engineer, you will also be expected to mentor others and effectively communicate your ideas to shape the future of AI at AMD.

To excel in this role, we seek a candidate with exceptional technical expertise, who can bridge deep proficiency in high-performance C++ software engineering and low-level GPU programming with a robust understanding of Large Language Models (LLMs) and AI systems. The ideal candidate can bridge kernel engineering with AI post-training (RL) experience. A great candidate is deep in one and light on the other.

Kernel engineering means demonstrating mastery in designing complex, scalable systems using modern C++, coupled with a fundamental grasp of GPU architectures (HIP/CUDA), memory hierarchies, and kernel optimization to maximize hardware performance. This expertise should be evidenced by significant hands-on experience in large-scale C++/HIP/CUDA projects, such as contributing to the ROCm ecosystem (e.g., rpp, MIVisionX, rocAL, rocdecode, rocjpeg), CUDA libraries (e.g., CV-CUDA, cuDNN, NCCL), or the C++/HIP/CUDA core of ML frameworks like PyTorch, TensorFlow, or JAX.

AI post-training is equally critical, and requires deep understanding of LLMs, including but not limited to transformer architectures, attention mechanisms, and the full model lifecycle, with hands-on experience in advanced model alignment and post-training techniques like Supervised Fine-Tuning (SFT) and Reinforcement Learning (e.g., RLHF, GRPO). Candidates must also stay at the forefront of LLM advancements, showing familiarity with cutting-edge trends such as Mixture-of-Experts (MoE) architectures, inference optimizations (e.g., quantization, speculative decoding), and modern application patterns like Agentic AI systems (e.g. AlphaEvolve for code/kernel generation).

Experience and interest in code generation and/or self-improving LLMs is a plus.

Benefits offered are described: AMD benefits at a glance.