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microTECH Global Limited

City Of Edinburgh / Global

AI Compiler Optimization Engineer - Edinburgh

  • £90000

Job Description

We are seeking a skilled AI Compiler Optimization Engineer to optimize AI model inference performance through advanced compiler technologies. You will focus on performance tuning for CPU or hybrid CPU/XPU heterogeneous architectures, profiling AI frameworks to discover new optimization opportunities, and delivering cutting-edge insights from industry research.

Key Responsibilities:

Compiler-Based Performance Optimization:

  • Implement compiler techniques (e.g., MLIR level optimizations, LLVM backend optimizations) to enhance inference performance on CPU and CPU/XPU hybrid systems

  • Optimize JIT level compute graphs with operator fusion, memory allocation and etc. for latency/throughput improvements

  • Preferred: Experience with LLVM/MLIR development

AI Model Profiling & Framework Optimization:

  • Profile end-to-end inference workflows on frameworks like TensorFlow, PyTorch, ONNX, and llama.cpp to identify hotspots and bottlenecks

  • Propose and implement optimization strategies (e.g., kernel tuning, graph-level optimizations)

  • Preferred: Experience optimizing models on multiple AI frameworks

Research & Insight Development:

  • Track and analyze the latest advancements in AI & compiler research (academic papers, open-source projects)

  • Produce actionable insight reports summarizing trends, benchmarks, and potential optimizations

  • Preferred: Strong technical writing skills with prior publications or reports

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