Software Engineer- GPU/AI/ML
Santa Clara, California$204kFull-timePosted 3mo ago
About the role
Senior software engineer role focused on GPU/AI/ML stack at AMD, spanning low-level kernel optimization through distributed training and inference, with emphasis on ROCm ecosystem and collaboration across hardware-software co-design.
Responsibilities
- Own the AI software stack: Establish best practices and drive performance from low-level GPU kernels to large-scale distributed systems. Use modern LLMs and agent-based tooling where it accelerates development and tuning of the ROCm ecosystem.
- Accelerate foundation models and agents: Improve training, post-training, and inference for LLMs and autonomous AI workloads so AMD is the default platform for the most demanding use cases.
- Co-design hardware and software: Partner on the full lifecycle—from GPU architecture input to software for new accelerators—and engage with the broader AI community to keep AMD at the forefront.
Qualifications
- Expert-level modern C++ and design of large, performance-critical systems.
- Strong grasp of GPU architecture, memory hierarchy, and kernel optimization (HIP/CUDA).
- Hands-on delivery on large-scale C++/HIP/CUDA codebases, such as ROCm (rocBLAS, hipDNN, Composable Kernel, AITemplate), the CUDA ecosystem (cuBLAS, cuDNN, CUTLASS, Thrust, CUB, NCCL), and ML framework cores such as PyTorch, TensorFlow, or JAX (C++/HIP/CUDA paths).
- Comfort diagnosing bottlenecks with profilers (ROCm Profiler, Nsight) in multi-GPU, distributed settings.
- Deep understanding of transformers, attention, and the full model lifecycle.
- Hands-on work in alignment and post-training—for example, SFT, RLHF, and GRPO.
- Awareness of MoE, quantization, speculative decoding, and agentic systems.
- Experience optimizing post-training and inference pipelines at scale.
- Substantial professional experience in performance-critical software development.
- Extensive HIP/CUDA experience optimizing DL and OSS LLM kernels and operators.
- Strong technical ownership and a track record of shipping complex systems.
- Clear communication and influence across teams.
- Plus: Familiarity with AMD ROCm/HIP ecosystem.
- Plus: RTL design and Verilog/SystemVerilog knowledge for hardware–software co-design.
Skills
Required:C++GPU kernel optimizationHIP/CUDAROCm/rocBLAS/hipDNN/Composible KernelCUDA ecosystem (cuBLAS, cuDNN, CUTLASS, Thrust, CUB, NCCL)ML frameworks integration (PyTorch, TensorFlow, JAX)Profiling tools (ROCm Profiler, Nsight)Transformers & ML lifecyclePost-training & fine-tuning (SFT, RLHF)
Nice to have:MoE/quantization/agentic systems
Benefits
- Benefits offered are described: AMD benefits at a glance.
Last updated Oct 15, 2026. Interested? Apply on the company site.
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