Optimization Engineer, Working Student (m/f/d)

Role overview Improve the mathematical quality and practical performance of an optimization pipeline used to prepare problems for different solvers. The working student will develop and implement methods spanning formulation changes, pre-solve reductions, and solution repair, with much of the work supporting quantum solvers.

Responsibilities - Design mathematically valid reformulations so problem instances fit the requirements of different solver classes. - Preprocess models by tightening formulations, removing redundant constraints, and deriving valid constraints that reduce search effort. - Improve solver outputs with local search, greedy heuristics, and feasibility repair. - Provide rigorous reasoning that proposed transformations preserve correctness. - Implement methods in the pipeline and consider runtime and memory use.

Requirements - Enrolled in mathematics, computer science, physics, or a related field; later bachelor’s or master’s study is a good fit. - Strong mathematical foundation, especially in combinatorial optimization and linear or integer programming. - Ability to identify subtle errors in reformulations and explain why they are incorrect. - Strong Python skills and enough Rust or C++ to navigate an existing codebase. - Interest in quantum computing and optimization. - Based in Germany, with remote work possible, or near Munich.

Nice to have - Familiarity with decomposition methods such as Benders or pre-solve tools such as PaPILO.

Benefits and work setup - Flexible work arrangements that can adapt to study and exam schedules. - Opportunity to shape the optimization pipeline and work where mathematical methods meet production software. - Munich office option, small supportive team, regular team events, and fitness membership.