SICK is one of the world’s leading solutions providers for sensor-based applications in the industrial sector. Founded in 1946 by Dr.-Ing. e. h. Erwin Sick and headquartered in Waldkirch im Breisgau near Freiburg, the company is a technology and market leader with 63 subsidiaries and affiliates as well as numerous agencies around the globe. SICK has more than 10,000 employees worldwide and generated a group revenue of EUR 1.8 billion in the 2025 fiscal year.
Job Description
Master Thesis: Robust AI inference within a WebAssembly Engine

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
Information at a Glance
Apply now
Requisition-ID:  37733
Posting Job Location:  Waldkirch (near Freiburg)
Full-time/Part-time:  Full-time

Contact: Sarah Disch

Discover all benefits

At SICK, we see people, not gender. 
We put great emphasis on diversity, reject discrimination and do not think in categories such as gender, ethnicity, religion, disability, age or sexual identity.