Work Location: Pisa, Italy
Contract Type: Full-time, On-site
Responsibilities:
-Drive the technological evolution of proprietary MBD toolchains toward AI-assisted workflows.
-Advance capabilities in large-scale efficient simulation, optimized code generation, and automated test generation.
-Lead the integration of LLMs and agentic workflows into the engineering design process.
Requirements:
-Education: M.Sc. in Engineering; a PhD is strongly preferred.
-Domain Expertise: Minimum 10 years of experience with commercial MBD tools used in PLC or energy domains (e.g., platforms similar to Siemens, Schneider Electric, Beckhoff, or GE).
-Programming: Excellent command of Java and strong proficiency in Python.
-MBD Technical Skills:
-Expertise in model-driven engineering: model-to-text, text-to-model, and model-to-model transformations.
-Deep knowledge of code generation for embedded devices (e.g., XText, Acceleo, Model-Intermediate representations) and code optimization techniques.
-Familiarity with modeling languages and frameworks: UML, Simulink/Stateflow, and Eclipse Modeling Framework (EMF).
-Experience with MIL/SIL (Model/Software-in-the-loop) simulation environments.
-Proven ability to solve complex optimization problems (e.g., MILP, Simulated Annealing, Genetic Algorithms).
-AI & ML Expertise:
-Hands-on experience with AI frameworks: TensorFlow, PyTorch, CUDA, LangChain, or Docling.
-Practical experience in Prompt Engineering, Fine-tuning, Reinforcement Learning, and Model Quantization.
-Experience building efficient multi-agent AI architectures (including RAG and orchestration) and integrating them into production-grade software.
-Professional Skills: Excellent communication, high level of initiative, and strong self-organization.
-Language & Travel: Fluency in English. Ability to work in a multi-cultural environment and availability for occasional international travel (within Europe and overseas) for several weeks at a time.
If this sounds of interest, please reach out to #
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