September 2025: Stability and quantization improvements for microsoft/onnxruntime. Key deliverables include stabilizing ONNX attention tests by relaxing tolerances to reduce CI false negatives, and fixing per-channel quantization in QNN models (removing unnecessary workarounds and correcting uint symmetric zero-points). Impact: improved CI reliability, faster iteration cycles, and more accurate quantization for production deployments. Technologies demonstrated include ONNX Runtime, QNN quantization, test tolerances, and CI automation.

August 2025 Monthly Summary (microsoft/onnxruntime and microsoft/Olive) Key features delivered: - CI/CD Pipeline: Upgraded QNN SDK to v2.37.0 in Azure pipelines for microsoft/onnxruntime to unlock compatibility with latest features and improvements; commit f8c6262399e2c7e0a58cd494f0e58d4f4262dc43. - QAIRT MHA2SHA transformation pass: Implemented in Olive to optimize ONNX model splits for Qualcomm NPUs; includes Python implementation files and comprehensive unit tests; commit 6457911511dcadfdd5f1e0cd5757571ddfd32419. Major bugs fixed: - No major bugs reported in the provided scope for August 2025. Overall impact and accomplishments: - Strengthened cross-repo collaboration and readiness for hardware-accelerated inference on Qualcomm NPUs; reduced deployment friction by keeping tooling up-to-date; improved potential performance through model-split optimization. Technologies/skills demonstrated: - Azure DevOps CI/CD, QNN SDK integration, Olive framework enhancements, QAIRT modernization, Python development, unit testing, ONNX optimization, NPU-focused performance considerations. Business value: - Accelerated release cycles with up-to-date SDKs, improved runtime efficiency on target NPUs, and decreased risk from outdated tooling.