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Master Thesis: Robust AI inference within a WebAssembly Engine

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📅 04/08/2026
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Winter Semester 2026/27 - limited to 5-6 month YOUR TASKS Familiarization with the basics of WebAssembly (Wasm), bytecode structures, and AI inference workloads Analysis of WebAssembly bytecode in the context of AI inference Investigation of the data flow of AI inference bytecode during execution in a selected Wasm engine Identifying potential for expansion in the Wasm engine to increase robustness, fail-safety, and reliability Designing and prototyping approaches for data flow monitoring of AI inference within a WebAssembly engine. YOUR PROFILE Master's degree in computer science or a comparable field of study Good knowledge of C++ and/or Rust Good knowledge of machine learning models and their architectures Ideally, initial experience in compiler construction, software engineering principles, and/or system development Interest in compiler construction, software engineering, and system software in the context of AI inference Contact: [[recruiterName]]
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