Permanent ONNX Jobs in Scotland

3 of 3 Permanent ONNX Jobs in Scotland

Senior / Staff Software Engineer (AI / Compiler)

edinburgh, central scotland, United Kingdom
Flux Computing
or MLIR Work with hardware teams to ensure the software stack fully leverages the capabilities of our OTPU architecture Extend ML frameworks (e.g. PyTorch, ONNX, OpenXLA) to better support performance-critical inference paths Lead design reviews, mentor engineers, and promote best practices in HPC and performance engineering Stay on the … applications Hands-on experience with ML compilers (e.g. LLVM, MLIR), and knowledge of runtime and scheduling optimisations Practical knowledge of ML frameworks like PyTorch, ONNX, or OpenXLA, and how to optimise their execution Experience scaling AI workloads across clusters or custom infrastructure—not just deploying on standard cloud setups Strong More ❯
Posted:

Senior / Staff Software Engineer (AI / Compiler)

glasgow, central scotland, United Kingdom
Flux Computing
or MLIR Work with hardware teams to ensure the software stack fully leverages the capabilities of our OTPU architecture Extend ML frameworks (e.g. PyTorch, ONNX, OpenXLA) to better support performance-critical inference paths Lead design reviews, mentor engineers, and promote best practices in HPC and performance engineering Stay on the … applications Hands-on experience with ML compilers (e.g. LLVM, MLIR), and knowledge of runtime and scheduling optimisations Practical knowledge of ML frameworks like PyTorch, ONNX, or OpenXLA, and how to optimise their execution Experience scaling AI workloads across clusters or custom infrastructure—not just deploying on standard cloud setups Strong More ❯
Posted:

Senior / Staff Software Engineer (AI / Compiler)

aberdeen, north east scotland, United Kingdom
Flux Computing
or MLIR Work with hardware teams to ensure the software stack fully leverages the capabilities of our OTPU architecture Extend ML frameworks (e.g. PyTorch, ONNX, OpenXLA) to better support performance-critical inference paths Lead design reviews, mentor engineers, and promote best practices in HPC and performance engineering Stay on the … applications Hands-on experience with ML compilers (e.g. LLVM, MLIR), and knowledge of runtime and scheduling optimisations Practical knowledge of ML frameworks like PyTorch, ONNX, or OpenXLA, and how to optimise their execution Experience scaling AI workloads across clusters or custom infrastructure—not just deploying on standard cloud setups Strong More ❯
Posted: