Applied AI Frameworks Engineer

Intel Intel · Semiconductors · Bangalore, India

Engineer to design and develop features for Intel's AI frameworks software stack, focusing on inference serving frameworks (SGLang, vLLM) and ML frameworks (PyTorch, Tensorflow, JAX). The role involves optimizing software for Intel's AI accelerators and GPUs, enhancing training and inference capabilities, and contributing to open-source communities.

What you'd actually do

  1. Design and develop SW features for AI frameworks - both HW-agnostic and HW-aware, like 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 and open-source software.

Skills

Required

  • Advanced C++ (C++ 14/17)
  • Python
  • parallel programming
  • machine learning kernels such as GEMM, Convolution, Flash attention
  • SGLang
  • vLLM
  • Deep Learning models/LLMs for text, vision, NLP
  • debug complex issues in multi layered SW systems
  • SW integration in large open-source frameworks
  • computer architecture
  • HW-SW optimization techniques
  • frameworks/platforms that have gone to production

Nice to have

  • Triton based kernels
  • compiler algorithms for heterogeneous system
  • Fuser optimizations
  • Inference serving framework architecture and functionality

What the JD emphasized

  • frameworks such as SGLang, vLLM
  • Deep learning training, and Inference capabilities
  • performance of Deep learning workloads
  • Intel's AI accelerators
  • next generation GPUs
  • production

Other signals

  • optimizing software stack
  • state of the art AI workloads
  • Intel's AI accelerators
  • next generation GPUs
  • Deep learning training, and Inference capabilities
  • performance of Deep learning workloads
  • Open-source community