Principal / Senior GPU SW Performance Engineer — Post‑Training Job Listing at AMD in San Jose, CA (Job ID 84572-en-us)

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.  

Principal / Senior GPU Software Performance Engineer — Post‑Training 

THE ROLE:

Drive the performance of post-training workloads on AMD Instinct™ GPUs. You'll work across kernels, distributed training, compiler and framework integrations, and AI-assisted engineering workflows to deliver fast, stable, and reproducible fine-tuning and RL training pipelines on ROCm.

This role is centered on hands-on performance engineering, with the added expectation that you can apply agentic and AI-assisted workflows to accelerate profiling, root-cause analysis, experiment orchestration, regression triage, and optimization at scale.

THE PERSON:

The ideal candidate is passionate about software engineering and the craft of training performance. You lead sophisticated cross-stack issues—spanning data pipelines, kernels, distributed training, runtime behavior, and compilers—to clear resolution. You communicate crisply and collaborate effectively with framework, compiler, kernel, and model teams across AMD, driving measurable improvements with rigor, ownership, and reproducibility.

You are also comfortable using AI-assisted and agentic workflows to improve engineering productivity: automating repetitive analysis, generating performance hypotheses, accelerating regression triage, and helping teams move faster while maintaining strong validation standards.

KEY RESPONSIBILITIES:

• Lead performance for fine-tuning and RL training solutions on AMD GPUs.
• Improve throughput, memory efficiency, and stability across data, model, optimizer, and runtime steps.
• Optimize multi-GPU and multi-node training performance, including communication and scaling behavior.
• Contribute efficient kernels/ops and targeted graph-level or runtime-level optimizations where they deliver the highest impact.
• Profile, diagnose, and resolve bottlenecks using standard tooling; prevent regressions in CI and benchmarking pipelines.
• Build and apply agentic or AI-assisted workflows to accelerate profiling analysis, experiment generation, regression triage, and performance debugging.
• Develop scalable tooling and automation to improve reproducibility, performance reporting, and optimization velocity across teams.
• Ship reproducible pipelines and documentation adopted by internal teams and external developers.
• Collaborate with framework, compiler, kernel, and model teams to land durable performance improvements.

PREFERRED EXPERIENCE:

• Proven GPU performance engineering for deep learning workloads (ROCm/HIP, Triton, or similar).
• Hands-on experience with SFT, LoRA, and RL-based training at scale.
• Strong PyTorch experience, including torch.distributed, FSDP/ZeRO, or equivalent distributed training approaches.
• Proficient in Python and C++; comfortable reading and writing kernels when needed.
• Experience with distributed systems and collective communication libraries.
• Track record of turning profiles into fixes, upstreaming changes, and documenting measurable results.
• Experience building or using AI-assisted developer workflows, agentic tooling, or automation for performance analysis, experiment management, or engineering productivity is a plus.
• Ability to balance deep technical investigation with practical automation and cross-functional execution.

ACADEMIC CREDENTIALS:

B.S., M.S., or Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or equivalent.

LOCATION:

San Jose, CA preferred. Other U.S.-based locations may be considered.

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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.