Senior Staff Software Engineer At AMD, we believe technology can change lives for the better. It can heal us, entertain us, and make us more connected, productive, and understanding of the world around us. And we're looking for talent who feel the same: people who want to leave the planet better than they found it, those who don't shy away from humanity's challenges but are determined to help solve them.
AMD is powering the next generation of supercomputing, high-performance computing, cloud, and AI. Whether you're designing next-gen processors, enabling AI breakthroughs, or creating go-to-market plans, every role at AMD contributes to something bigger — technology that moves the world forward.
AMD is looking for a senior staff software engineer to join our growing team. As a key contributor you will be part of a leading team to drive and enhance AMD's abilities to deliver the highest quality, industry-leading technologies to market.
The ideal candidate possesses an innovative and problem-solving mindset, has a keen eye for software engineering development, and is diligent and passionate about technology. A successful candidate will need to employ strong knowledge in computer technologies, leadership skills in technical areas, and SW engineering expertise as well as a strong ability to compete effectively in a fast-paced, relevant environment while working with different teams of engineers and collaborators.
Key Responsibilities: Design and implement compiler optimizations using LLVM and/or MLIR targeting GPU architectures
Develop and optimize GPU kernels using CUDA, HIP, or similar parallel programming models
Analyze application performance, identify bottlenecks, and deliver end-to-end performance improvements across the stack
Collaborate with architecture, runtime, and framework teams to enable new hardware features and improve efficiency
Build tooling and methodologies for profiling, benchmarking, and performance analysis on GPU systems
Contribute to compiler code generation, IR transformations, and kernel scheduling to maximize hardware utilization
Preferred Qualifications: Experience with ML workloads, AI frameworks, or HPC systems
Familiarity with GPU kernel generation, memory hierarchy optimization, and low-level performance tuning
Experience working across hardware/software co-design and influencing architecture decisions
Strong understanding of GPU architecture and parallel computing concepts
Proficiency in C/C++ with experience in CUDA, HIP, or equivalent GPU programming models
Hands-on experience with compiler technologies (LLVM, MLIR, or similar)
Experience in performance analysis, profiling, and optimization of compute-intensive workloads
Solid understanding of compiler design, optimization techniques, and code generation
Academic Credentials: Bachelor's or Master's degree in Computer/Software Engineering, Computer Science, or related technical discipline
Location: San Jose, California
This role is not eligible for visa sponsorship.