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Sebastian Moßburger

PROFILE

Sebastian Moßburger

Worked across microsoft/onnxscript, pytorch/rl, and apple/containerization to deliver targeted improvements in deep learning infrastructure and deployment workflows. Addressed a bug in ONNX Script Rewriter by updating Python-based graph rewriting logic to correctly handle Slice operations with non-unit steps, adding regression tests to ensure reliability for downstream ONNX models. In pytorch/rl, refactored LSTM initialization using PyTorch to prevent faults from uninitialized hidden states, enhancing model stability. Contributed to apple/containerization by implementing environment-driven SSL TrustRoots configuration in Swift, improving security and flexibility for container registry interactions. Demonstrated strengths in debugging, test-driven development, and cross-domain machine learning engineering.

Overall Statistics

Feature vs Bugs

33%Features

Repository Contributions

3Total
Bugs
2
Commits
3
Features
1
Lines of code
113
Activity Months2

Work History

December 2025

2 Commits • 1 Features

Dec 1, 2025

December 2025 monthly summary focusing on key business value and technical achievements across two repositories: pytorch/rl and apple/containerization. Key outcomes include stabilizing model execution in RL through a bug fix in LSTM initialization and strengthening deployment security/configurability via environment-driven SSL TrustRoots configuration. These efforts reduce runtime faults, improve deployment flexibility, and support safer, more scalable ML workflows.

August 2025

1 Commits

Aug 1, 2025

August 2025 monthly summary for microsoft/onnxscript: delivered a focused bug fix to the ONNX Script Rewriter related to Slice operation handling when step != 1. Added a reproduction test and updated the rewrite rule to skip non-unit steps, ensuring correct Slice handling across varying step values. This enhancement reduces the risk of incorrect rewrites in ONNX export paths and improves reliability for downstream models and tooling that rely on accurate Slice semantics. Demonstrates effective debugging, test-driven development, and collaboration within the ONNX scripting pipeline.

Activity

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Quality Metrics

Correctness80.0%
Maintainability73.4%
Architecture80.0%
Performance66.6%
AI Usage20.0%

Skills & Technologies

Programming Languages

PythonSwift

Technical Skills

ContainerizationGraph RewritingNetworkingONNX RuntimePyTorchRNNsSwiftTestingdeep learningmachine learning

Repositories Contributed To

3 repos

Overview of all repositories you've contributed to across your timeline

microsoft/onnxscript

Aug 2025 Aug 2025
1 Month active

Languages Used

Python

Technical Skills

Graph RewritingONNX RuntimeTesting

pytorch/rl

Dec 2025 Dec 2025
1 Month active

Languages Used

Python

Technical Skills

PyTorchRNNsdeep learningmachine learning

apple/containerization

Dec 2025 Dec 2025
1 Month active

Languages Used

Swift

Technical Skills

ContainerizationNetworkingSwift