Senior Engineer Optimisation M/F

About

In this role you lead optimization topics within the IPM OneTech program, collaborating to design scalable optimization components for industrial energy projects. You translate business needs into robust optimization models and implement high-impact features with a focus on performance and reliability. You guide technical roadmaps, mentor junior engineers, and foster collaboration with external and academic partners. This position offers a chance to shape practical optimization solutions for decarbonization and grid-connected assets within a growing platform.

Responsibilities

• Act as technical lead for optimization topics: selections of algorithms, modeling approaches, tools, and ecosystems
• Design and develop advanced optimization methods for diverse industrial problems
• Contribute to the technical roadmap to ensure scalability, robustness, and maintainability of software
• Implement high-impact features improving performance and numerical stability
• Translate operational needs into robust optimization models in collaboration with business managers and experts
• Maintain links with external and academic ecosystems to monitor research and partnerships
• Evaluate and advocate external solutions aligned with product needs
• Provide mentorship and technical reviews to junior engineers and upskill the team
• Lead or contribute to advanced research activities and industrialization of optimization models
• Develop and maintain technical documentation and guidelines for optimization models and methods
• Contribute to external/internal visibility through technical communication and methodological guidance
• Drive adoption of optimization solutions across users and stakeholders
• Lead or contribute to the engineering and deployment of scalable software solutions

Qualifications

• 10+ years of experience in optimization and operations research
• Engineering degree in Mathematical Optimization / Operations Research
• Strong mathematical skills in optimization, numerical modeling, and statistics
• Expertise in MILP/MNLP formulations
• Solid grasp of combinatorial optimization, heuristics, and metaheuristics (GA, PSO, CMA-ES)
• Experience with solvers (Gurobi, CPLEX, CBC, IpOpt, GAMS) and modeling libraries (Pyomo, PuLP)
• Advanced Python programming and delivering industrial-grade software
• Experience with version control and collaboration tools (GitHub, GitLab, Azure DevOps)
• Professional working proficiency in English; French is a plus
• Knowledge of Machine Learning as a plus