Sr. Software Development Engineer

AMD AMD · Semiconductors · Beijing, China · Engineering

Senior Software Development Engineer focused on optimizing AI/ML models (CNN, Transformer, LLM, multimodal) for AMD hardware platforms. Responsibilities include developing quantization, low-precision, and compression features, building production-quality Python tools, and analyzing performance tradeoffs. Collaborates with researchers, framework engineers, and hardware experts.

What you'd actually do

  1. Design, implement, and maintain model optimization features for AI workloads on AMD hardware platforms.
  2. Develop quantization, low-precision, and compression capabilities for CNN, Transformer, LLM, and multimodal models.
  3. Build production-quality Python tools, libraries, APIs, and framework components.
  4. Support training and fine-tuning workflows for optimized models.
  5. Analyze and debug accuracy, latency, memory usage, and deployment tradeoffs.

Skills

Required

  • Strong software development skills
  • Hands-on experience in model compression and low-precision optimization
  • Ability to use AI-assisted tools effectively
  • Strong technical judgment and code quality
  • Experience with AI/ML frameworks
  • Experience with model optimization
  • Experience with quantization
  • Experience with efficient AI deployment on accelerator hardware
  • Python development and debugging skills
  • Solid understanding of CNN, LLM, or multimodal model architectures
  • Ability to reason about accuracy, performance, latency, memory footprint, and deployment constraints
  • Strong software engineering fundamentals

Nice to have

  • Experience in training workflows
  • Experience in runtime integration
  • Experience with PyTorch
  • Experience with ONNX/ONNX Runtime
  • Experience building production-quality tools, libraries, APIs, or framework components
  • Experience working with geographically distributed teams

What the JD emphasized

  • model optimization
  • quantization
  • low-precision
  • compression
  • AI deployment on accelerator hardware
  • CNN
  • Transformer
  • LLM
  • multimodal models
  • production-quality

Other signals

  • model optimization
  • quantization
  • low-precision
  • compression
  • AI deployment on accelerator hardware