Pisa Research Center plays a leading role within Huawei Group in researching new technologies and applications in the field of digital power and electric vehicles. The company is looking for an expert to enlarge its team in charge of developing next-generation Model-Based Design tools. In this role, you will be a system engineer designing and developing simulation, code generation and optimization tools for these domains, also integrating novel AI technologies. You will be joining a dynamic and highly collaborative team of experts and PhDs passionate about research projects and innovative solutions.
Work Location: Pisa, Italy
Type of contract: full-time, on-site (Pisa)
Position Responsibilities:
Drive the technological evolution of proprietary MBD tools towards AI-assistance, large-scale efficient simulation, optimized code and test generation.
Requirements:
· M.Sc in Engineering. PhD preferred
· Domain at least 10 years of experience on commercial MBD tools used in PLC or energy domains (e.g., Siemens, Schneider Electric, Beckhoff, General Electric)
· Knowledge of the most recent trends on MBD tools functionality and capability of driving the technological innovation of these tools for the energy domain.
· Programming languages knowledge of Java (excellent) and Python (good)
· MBD expertise:
o Expertise in model-driven engineering, including model-to-text, text-to-model and model-to-model transformations
o Expertise on code generation from models (e.g., XText, Acceleo, Model-Intermediate representations) for embedded devices and techniques to optimize the generated code
o Familiarity with modeling languages such as UML, Simulink/Stateflow tools (or similar), Eclipse-Modeling Framework (EMF)
o Experience on tools for MIL/SIL simulation
o Experience in solving optimization problems (through e.g., MILP, Simulated annealing, genetic algorithms, etc.)
· AI expertise:
o Experience on usage of AI frameworks (e.g., Tensorflow, CUDA, Pytorch, langchain, docling)
o Experience in prompt engineering, fine tuning, reinforcement learning, model quantization
o Experience in building efficient multi-agent AI architectures (including LLM, RAG and orchestration) and integration into products
· Excellent communication, own initiative and self-organization skills
· Fluency in English and ability to work in a multi-cultural environment
· Availability to travel in Europe and in China, even for a few weeks.
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