AI Framework Engineer
Core
Optimizing and developing deep learning frameworks for AMD GPUs to enhance training and inference performance across multi-GPU and multi-node systems.
Role type
Senior IC deep learning framework engineer (LLM/GPU)
Builds
Optimized deep learning and LLM inference frameworks for AMD GPU hardware
Domain
AI/ML infrastructure, High-Performance Computing, GPU architecture
Deliverable
production ML models
Required skills
C++ development, Python, GPU kernel optimization, LLM framework optimization, distributed systems, compiler technologies, profiling and performance engineering
Preferred skills
CUDA, HIP, Triton, LLVM, ROCm, FlashAttention, PagedAttention, quantization techniques
Technologies
TensorFlow, PyTorch, vLLM, SGLang, Llama, Qwen, DeepSeek, FlashAttention, PagedAttention, HIP, CUDA, Triton, LLVM, ROCm, CK, CUTLASS
Responsibilities
Optimize major DL/LLM frameworks (TensorFlow, PyTorch, vLLM, SGLang) for AMD GPUs; Develop and tune GPU kernels and performance-critical operators; Adapt and optimize LLM architectures (e.g., Llama, Qwen, DeepSeek) and apply advanced techniques like FlashAttention and quantization; Perform comprehensive profiling to identify bottlenecks and implement system, memory, and communication optimizations; Prototype and integrate emerging optimization methods into production systems; Collaborate with internal GPU library teams and open-source maintainers.
Seniority
Senior, hands-on IC
