Applied AI (frameworks) Engineer

Intel Intel · Semiconductors · Bangalore, India

Engineer to work on Intel's AI frameworks software stack, focusing on design, development, and optimization of features for AI accelerators and GPUs. This includes ML kernel development, enhancing training and inference capabilities, and contributing to open-source AI frameworks like PyTorch, Tensorflow, and JAX.

What you'd actually do

  1. Design and develop SW features for AI frameworks - both HW-agnostic and HW-aware, especially in ML kernel development.
  2. Enhance and extend the Deep learning training, and Inference capabilities in the Software stack.
  3. Identifying optimization opportunities in the software stack to enhance performance of Deep learning workloads
  4. Participate in discussions with Open-source community, involve in development, adopting upstream and Upstream software.

Skills

Required

  • Advanced C++ (C++ 14/17)
  • Intermediate skills of Python
  • parallel programming
  • developing machine learning kernels (GEMM, Convolution, Flash attention)
  • PyTorch, Tensorflow or JAX
  • Deep Learning models/LLMs for Vision / NLP
  • debug complex issues in multi layered SW systems
  • SW integration in large open-source frameworks
  • computer architecture
  • HW-SW optimization techniques
  • working on frameworks/platforms that have gone to production

Nice to have

  • developing and integrating CUTLASS or Triton based kernels in Large language models (LLMs)
  • compiler algorithms for heterogeneous system
  • Fuser optimizations

What the JD emphasized

  • experience in developing machine learning kernels such as GEMM, Convolution, Flash attention etc
  • In depth and hands on experience in one of the frameworks such as PyTorch, Tensorflow or JAX
  • Experience in working on frameworks/platforms that have gone to production

Other signals

  • optimizing state of the art Software stack for Intel's AI accelerators
  • enabling and optimizing Deep learning training, and Inference capabilities
  • ML kernel development
  • working on frameworks/platforms that have gone to production