Software Engineer, AI Engineer, Data Scientist

Experteer Overview In this role you will industrialize prototype computation code into a reliable, scalable software solution for Simulation & Process Data Management. You will work with cross‑functional teams to align physical models with industrial implementation, ensuring quality and traceability throughout the development lifecycle. You will optimize performance, automate processes, and document both technical and user aspects of the software.

This is a mission-driven opportunity to shape digital tools used in aerospace and defence simulations at a global industrial group.

Retribuzione / Benefits Industrialize prototype computation code into a robust software solution for industrial use Analyze and translate existing engineering code and models into maintainable implementations

Ensure code quality, performance optimization, automation, and traceability across the development lifecycle

Refactor code for readability, modularity, and computational efficiency

Implement automated testing (unit, integration, regression) and CI/CD pipelines

Prepare technical and user documentation (manuals, API docs, tutorials)
Integrate software into industrial workflows and containerized environments (Docker/Singularity)
Collaborate with R&D and engineering teams to align physical models with industrial implementation

Ensure software verification/validation in compliance with standards (ISO, ASME V&V etc.)Qualifications Master's degree in Engineering (Aerospace or Computer) or Physical Science Expert‑level experience (3–5 years)
Programming languages:
Python, C/C++, C#, Fortran Tools & environments:
Git, CMake, Jenkins/Git Lab CI, Docker, Linux Numerical and scientific computing: numerical methods, FEM/FVMPerformance optimization & parallel computing:
OpenMP, MPI, CUDA, or OpenACCSoftware engineering practices: modular design, testing, code review, documentation

HPC environments: job schedulers (Torque, PBS, etc.) and distributed computing

Ability to analyze existing code (Python, Fortran, C/C++, MATLAB) and understand underlying models

CI/CD, automated testing, and documentation expertise

Version control (Git, Git Lab/Git Hub) and containerization in workflows
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