AI Software Architect

1 week ago

Bengaluru, Karnataka, India Intel Full time ₹ 12,00,000 - ₹ 36,00,000 per year

We are looking for a dynamic and passionate hands-on senior contributor to join Intel's AI Group.

Day-to-day work involves contributing to open-source AI frameworks such as PyTorch and inference-serving frameworks like vLLM and SGLang.

The role includes designing, developing, and optimizing features for Intel's AI framework software stack for Intel's AI accelerators and next-generation GPUs.

Roles and Responsibilities include:

  • Design and develop software features for AI frameworksboth hardware-agnostic and hardware-aware.
  • Enhance and extend deep learning inference and training capabilities in the software stack.
  • Analyze and architect state-of-the-art features across different frameworks and drive development across the full software stack.
  • Identify optimization opportunities in the software stack to improve the performance of deep learning workloads.
  • Participate in discussions with the open-source community, contribute to development, and upstream software enhancements.

*Qualifications:*

  • B.Tech or M.S./M.Tech in CS, ECE, or related fields with 612 years of overall experience.
  • Proficient in Python-based complex software implementations; intermediate knowledge of advanced C++ (C++14/17) and parallel programming.
  • In-depth, hands-on experience with frameworks such as PyTorch, vLLM, and SGLang.
  • Experience with advanced inference-serving features such as disaggregated serving, quantization, speculative decoding, and constrained decoding.
  • Strong understanding of LLMs
  • Practical knowledge of deep learning models for image and video generation is desirable.
  • Ability to debug complex issues in multi-layered software systems; understanding of software integration in large open-source frameworks.
  • Strong understanding of computer architecture and HW-SW optimization techniques.
  • Effective communication skills and experience working in cross-geo teams.
  • Ability to perform performance analysis of code on both host and accelerators/GPUs using open-source and proprietary profilers.
  • Understanding of the competitive landscape for technologies in this domain.

Preferred

  • Experience developing and integrating CUTLASS or Triton-based kernels for deep learning.
  • Knowledge of compiler algorithms for heterogeneous systems and fuser optimizations.

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