Sr. Software Development Engineer (GPU Machine Learning Performance)

Responsibilities THE ROLE

AMD’s Advanced Technology Group is an entrepreneurial research and development team to build AMD's future advanced platforms & products. Our teams work closely with outside customers and internal teams to develop hardware, software, and systems solutions into next generation computing platforms. As part of AMD Advanced Technology Group, you will have the opportunity to be part of a winning team that will collaborate with internal teams & customers, explore new platform technologies, and lead the development of best-in-class hardware, software, and systems technologies that our customers will use for real-world problems.

In this role, you will join our team working on AMD’s next generation GPU edge inference solutions, ensuring machine learning solutions hit performance goals through GPU performance analysis, profiling, workload optimization and other duties to unlock powerful experiences for end-users with AMD devices. THE PERSON:

AMD is looking for a seasoned Senior Staff Member, to join our Advanced Technology Group GPU based Machine Learning development to work on AMD’s long-term Graphics and Machine Learning solutions, which will have significant impact for AMD, and the future of our products. Our group works on forward-looking projects and novel system concepts that significantly impact AMD’s future product portfolio.

Your role will contribute to shaping AMD’s forward-looking hardware and software technologies.

KEY RESPONSIBILITIES

• Work within a team on Machine Learning SW and Workload development in pre and post-silicon phases of product development enabling next-generation of ML workloads in functional and performance attainment.
• Profile end‑to‑end inference pipelines to identify performance bottlenecks spanning kernels, scheduling, memory behavior, and model execution logic.
• Optimize execution paths for transformer models, including attention computation, KV‑cache behavior, and efficient memory layouts.
• Develop and refine strategies for batching, parallelism, quantization, and distributed execution across single‑node and multi‑node environments.
• Collaborate with compiler, kernel and user mode driver teams, and hardware architecture teams to improve system‑level efficiency and remove scaling blockers.
• Build performance models, benchmarking suites, and automated evaluation tools to quantify gains and track regressions.
• Shape best practices for profiling, debugging, and performance tuning across engineering teams.
• Communicate results, insights, and recommendations clearly to both technical and non‑technical partners.
• Contribute to AMD’s next-generation GPU Machine Learning technologies.

PREFERRED EXPERIENCE

• Strong experience in high‑performance GPU computing, inference optimization, or systems‑level performance engineering.
• Deep understanding of machine learning architectures and large‑scale inference behavior.
• Demonstrated success in building, optimizing, Machine Learning kernels, workloads, models for performance and power.
• Proficiency in GPU profiling tools, memory analysis, and performance tracing (e.g., HIP/CUDA profiling tools, custom instrumentation).
• Ability to reason about compute/memory tradeoffs, kernel scheduling, KV‑cache patterns, and parallel execution models.
• Hands‑on experience with GPU kernels, inference runtimes, or compiler‑adjacent optimizations.
• Demonstrated track record of delivering measurable performance improvements in complex systems.
• Ability to drive technical direction in ambiguous or rapidly evolving problem spaces.
• Track record in using AI tooling to accelerate engineering work.
• Strong collaboration and communication skills.

ALTERNATE LOCATION

• Austin, TX Qualifications Benefits offered are described: AMD benefits at a glance. This posting is for an existing vacancy.