Senior Operations Research Engineer

• Design and implement mathematical optimization models for complex industrial problems
• Develop algorithms for planning, scheduling, routing, allocation, and decision support
• Collaborate with machine learning engineers to combine optimization techniques with AI solutions
• Build scalable optimization pipelines using Python and modern software engineering practices
• Validate optimization models through simulation and experimentation
• Analyze algorithm performance and continuously improve solution quality and computational efficiency
• Work closely with cross-functional teams to understand business objectives and translate them into mathematical models
• Document approaches, assumptions, and experimental results to support knowledge sharing and future development

• MSc or PhD in Operations Research, Applied Mathematics, Industrial Engineering, Computer Science, or another STEM discipline
• Strong knowledge of optimization techniques such as linear programming, mixed-integer programming, constraint programming, nonlinear optimization, or heuristic/metaheuristic algorithms
• Experience translating business problems into mathematical optimization models
• Strong Python programming skills
• Experience with LLMs
• Ability to combine optimization workflows with LLM automation
• Experience building production-quality software rather than research prototypes only
• Experience working with large datasets and developing efficient optimization workflows
• Strong analytical thinking and problem-solving skills
• Ability to work independently in an R&D environment with evolving requirements
• Good communication skills and fluent English
• Experience with machine learning or AI-assisted optimization is nice to have
• Experience with simulation, stochastic optimization, agent-based modeling, or Markov models is nice to have
• Knowledge of high-performance computing (HPC) is nice to have
• Experience with cloud platforms and distributed computing is nice to have
• Experience with industrial optimization problems such as logistics, manufacturing, energy, robotics, or supply chain is nice to have

• Private health insurance
• Well-being programs
• Flexible and hybrid work models
• Laptops and gear
• Training
• Language classes
• Social events
• Great offices
• Equal opportunities in recruitment, career development, and leadership