Lead AI Compiler Engineer

We are looking for an AI Compiler Engineer to join this high impact team working in the growing field of on-device AI inference acceleration as an individual contributor or as a technical lead in the AI group (AIG).

As an AI Compiler Engineer, you will design and optimize AI compiler stack and tools that enable efficient execution of state-of-the-art open source as well as proprietary AI models such as LLMs, transformer models, etc., to AMD NPUs for on-device AI inference use-cases.

You will work on transforming high-level AI models into efficient, low-level code that can run on NPU.

Your work will directly impact the performance, efficiency, and scalability of our AI solutions.

SCOPE OF WORK:

• Operator Fusion:

  Identify and implement performance optimization opportunities by reducing memory traffic through operator fusion at different memory hierarchy levels, e.g., attention block.

• Problem Partitioning and Dataflow Orchestration:

  Design of algorithms to optimally map given AI operation to the NPU comprising of an interconnected array of AI engines.
• Design and implementation of algorithms to orchestrate dataflow through multi-level memory hierarchy.

• Kernel Design and Development:

  Design and implement highly optimized C++/intrinsic based kernels for AI related operators.
• Develop vectorized code that leverages

  SIMD (Single Instruction, Multiple Data)

  and

  VLIW (Very Long Instruction Word)

  for optimal performance.
• Perform performance, program memory, and accuracy tradeoffs.

• Testing and Validation:

  Develop CPU models for the ML operators in C++/Python to validate accuracy.
• Write unit tests and integration tests to ensure correctness and reliability.

• Performance Profiling and Tuning:

  Profile and analyze the performance of model layers.
• Identify performance/accuracy bottlenecks and alleviate those.

• Documentation and Collaboration:

  Effective technical communication of day-to-day work and document design specs.
• Follow good coding practices, using version control system.
• Collaborate with cross-functional teams spanning over AI research, core architecture, and software engineering.

REQUIRED SKILLS:

• Excellent

  C/C++ and Python coding skills

  .
• Good understanding of

  SIMD, VLIW processor architecture

  .
• Experience with

  vectorized programming (SIMD)

  .
• Thorough understanding of

  fixed and floating point arithmetic

  .
• Good understanding of various operators in state-of-the-art AI models.
• Knowledge of low-level hardware details (

  cache hierarchy, DMA programming

  ).
• Excellent problem-solving skills, especially on debug, and a passion for on-device AI.
• Prefer candidates with past experience on

  AI compiler design

  .