Advanced Micro Devices, Inc-posted 3 months ago
San Jose, CA
5,001-10,000 employees

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.

  • Provide technical leadership in the development of various AI frameworks in the AMD ecosystem.
  • Drive technical direction for next generation frameworks for AI model training and inference for a variety of AMD devices.
  • Enhance AI framework capabilities to enable cutting-edge models on AMD hardware.
  • Collaborate closely with AI researchers to develop framework components for efficient mapping of AI models to hardware accelerators.
  • Guide other senior developers and domain experts in the development of next generation framework software.
  • Experience with development in AI frameworks, AI runtime stacks, and/or performance tuning for workloads on ML accelerator hardware.
  • Experience with ML frameworks such as PyTorch, OnnxRuntime, JAX, TensorFlow.
  • Proficient in C++ programming.
  • Experience developing and debugging in Python.
  • Experience with AI model architectures, e.g. Transformers, CNNs.
  • Team player ready to work with a geographically distributed team.
  • Knowledge of custom accelerator hardware.
  • Experience with AI software framework, benchmarking and profiling.
  • Operator/kernel development and deployment of models to accelerator (GPU/NPU) stack.
  • Depth of experience with model optimization, including quantization and sparsity.
  • Understanding of model architectures, LLMs, MoE, diffusion.
  • AMD benefits at a glance.
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