Principal / Senior GPU SW Performance Engineer — Post‑Training

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.

Drive the performance of  post‑training  workloads on AMD Instinct™ GPUs. You’ll work across kernels, distributed training, and framework integrations to deliver fast, stable, and reproducible training pipelines on ROCm.   THE PERSON:   The ideal candidate is passionate about software engineering and the craft of  training performance . You lead sophisticated cross‑stack issues—spanning data loaders, kernels, distributed training, 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.

Lead performance for  finetuning and RL  training solutions on AMD GPUs. Improve  throughput, memory efficiency, and stability  across data, model, and optimizer steps. Optimize  multi‑GPU/multi‑node  training and communication patterns. Contribute  efficient kernels/ops  and targeted graph‑level optimizations. Profile, diagnose, and resolve  bottlenecks using standard tooling; prevent regressions in CI. Ship  reproducible pipelines and documentation  adopted by internal teams and external developers. Collaborate with  framework, compiler, and model  teams to land durable improvements.

Proven  GPU performance engineering  for deep learning (ROCm/HIP, Triton, or similar). Hands‑on with  SFT. LoRA  and  RL‑based training  at scale. Strong  PyTorch  experience (torch.distributed, FSDP/ZeRO or equivalent). Proficient in  Python  and  C++ ; comfortable reading/writing kernels when needed. Experience with  distributed systems  and collective communication libraries. Track record of  turning profiles into fixes , upstreaming changes, and documenting results.   ACADEMIC CREDENTIALS:   B.S./M.S./Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or equivalent     LOCATION: San Jose, CA preferred. Other US based locations may be considered.   #LI-MV1 #HYBRID     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.