Applied Operations Research Engineer

About the role

We are building the world's decision infrastructure: the strategic twin of every industrial organization for complex combinatorial problems. We unlocked what wasn't possible before: mapping reality with its levers and constraints into a computer, then running n-dimensional optimization on critical value-chain decisions. We help Europe stay strong and the German Mittelstand make good decisions between market shifts, orders, machines and people.

What you’ll do

• Hi, I'm Erik, CTO of Circonomit. This ad is specific on purpose: you should be able to tell from it whether this is your job.
• That bridge is your mission. You work with our math and OR team to translate real customer problems into models, and you develop the engine that runs them.
• We will not sugarcoat it: combinatorial search is unpredictable, customer data arrives messy, and some weeks a deadline sets the priority.

What they’re looking for

Select a requirement to inspect fit, evidence or application context.

• You have modeled and shipped combinatorial optimization in industry (MILP, CP, or both), with models that survived messy data, deadlines and real users.
• Algorithm design you have actually shipped: you know where methods and solvers reach their limits, CP-SAT and Gurobi included, and you can say which technique bought you what, from warm starts and rolling horizon to relax-and-fix, aggregation, matheuristics, or a plain heuristic when an exact solve is the wrong tool.
• You have run optimization workloads where someone was waiting on the answer, not only in notebooks: cancellation, timeouts and parallel solves are problems you have already solved once.
• Python at production quality: tests, types, review, and a profiler before an optimizer. You know how numerics go wrong where a model meets a solver: scaling, tolerances, integrality, and the moment money stops fitting in an integer.
• You want to understand the customer's problem and their data, not only the model.
• You have worked in a team, not mostly alone.
• German at C1 or better, and fluent English. Team life runs in German; code and docs are English.
• NRW-based (Cologne office), optionally Munich, Stuttgart, Berlin area or else willing to work hybrid. Open to find a way if we fit.
• Nice to have: solver internals · performance work on numerical or compiled code · DSL or compiler work · production planning, supply chain or logistics domain knowledge.
• You are structured and biased for action, and you have shown you play to win wherever life has put you so far.
• This role is not for you if you want research freedom over product deadlines, if you would rather rewrite an engine than measure it, if you want to work only inside your own abstraction, if the data work is someone else's job, or if you are waiting for the next task to be handed to you.