6 of 6 Permanent LLVM Jobs in Edinburgh

diversified team with different culture background but share common goals. Your contribution can be up-streamed to open-source communities. Key Responsibilities: Develop LLVM based compilers: Enable compiler for new architecture features Design & implement optimization for xPU architectures Use AI technology to help compiler optimize Analyze performance of compiler ...

Helpful, but not required: Experience with ML graph optimizations, parallel/distributed programming, heterogeneous ML computation, and/or code generation. Exposure to MLIR, LLVM, and/or the Mojo programming language. Advanced degree in Computer Science or a related area is a plus. What Modular brings ...

microTECH Global Limited in the United Kingdom is seeking an AI Compiler Optimization Engineer to push inference performance on CPU and hybrid CPU/XPU systems. You will implement advanced compiler techniques and profiling to ...

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 … 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 ...

microTECH Global Limited in the UK is seeking a dedicated compiler engineer to join a distributed team in Cambridge and Edinburgh. You will develop LLVM-based compilers and libraries, tackle real‐world server, HPC and AI computing problems, and contribute changes upstream to open‐source communities. The role focuses ...

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 … 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 ...