Principal Software Engineer – PyTorch Training Frameworks

The Role

At AMD, we are seeking a Principal-level PyTorch training framework expert to drive performance, scalability, and correctness of large-scale AI training on AMD Instinct™ accelerators. You will work at the intersection of PyTorch internals, distributed training, and hardware-aware optimization, collaborating closely with compiler, kernel, driver, and architecture teams.

Key Responsibilities

• Act as a technical authority for PyTorch training at AMD, setting direction for performance, scalability, and reliability.
• Drive optimization of key PyTorch training workloads (LLMs/foundation models) across single-node and multi-node systems.
• Improve and debug training performance in areas such as DDP/FSDP, gradient checkpointing, mixed precision, memory planning, and communication/computation overlap.
• Partner with ROCm compiler/runtime, kernel, and driver teams to resolve performance bottlenecks and correctness issues across the full stack.
• Contribute to and influence upstream PyTorch (design discussions, code contributions, performance fixes, CI/debug).
• Develop and maintain representative training benchmarks, profiling workflows, and performance regression detection for key models.
• Lead deep-dive investigations of performance regressions and hard correctness issues; drive cross-team resolution to closure.
• Mentor engineers and raise the bar on framework-quality code, performance engineering practices, and technical rigor.
• Engage with strategic customers/partners on training enablement, root-cause analysis, and best-practices for AMD platforms.

Preferred Experience

• Deep experience with PyTorch internals and training systems (Autograd, optimizers, dataloading, compilation paths, runtime behavior).
• Strong distributed training expertise: DDP, FSDP, tensor/pipeline parallel concepts, collectives (NCCL/RCCL), multi-node debugging.
• Proven track record in performance engineering (profiling, tracing, kernel/runtime analysis, memory optimization, scaling studies).
• Strong programming skills in Python and C/C++ (ability to land clean, maintainable changes in large codebases).
• Familiarity with PyTorch ecosystem components such as TorchInductor / torch.compile, Triton, CUDA/HIP-style programming models, and performance tooling.
• Experience working across OS/hardware boundaries in Linux-based environments (containers, CI, drivers/runtimes are a plus).
• Clear technical communication: design docs, code reviews, stakeholder updates, and cross-team coordination.
• Demonstrated ability to lead through influence (principal-level impact, mentoring, and architectural decision-making).

Location

San Jose, Seattle or Austin are preferred US locations (hybrid).

Benefits

AMD offers competitive benefits including:

• Health insurance
• Retirement plans
• Flexible spending accounts
• Employee assistance programs
• Professional development opportunities