Applied Operations Research Engineer

About This Opportunity

We are representing a well-funded industrial optimization software company in Germany. Our client builds decision-support platforms for manufacturing and production planning—solving complex combinatorial problems at scale for mid-market and enterprise customers across Europe.

This is a core technical role: you will translate real-world planning constraints into optimization models, own the engine that solves them, and ensure the output is accurate, fast, and usable by non-technical planners.

Responsibilities

• Design and implement optimization models for production planning, capacity scheduling, and resource allocation problems using MILP, constraint programming, or hybrid approaches
• Build and maintain the modeling engine—defining abstractions, vocabularies, and interfaces that let engineers and eventually customers extend models without specialist support
• Handle end-to-end data integration from ERP systems and spreadsheets, including validation, cleaning, and error-surfacing before models run
• Deliver solutions that scale: from single-site problems to multi-site, multi-period models running under hard constraints, and infrastructure that supports concurrent solves for many customers
• Own your work from first commit to production deployment and ongoing operation
• Produce outputs planners can understand and defend—optimization results with transparency into trade-offs, infeasibilities, and sensitivity

What We're Looking For

Required:

• Proven experience shipping combinatorial optimization models in industry (MILP, CP, or both) that handled messy data, real users, and production deadlines
• Practical algorithm design: you understand solver limitations (CP-SAT, Gurobi, or similar) and have applied techniques like warm starts, rolling horizon, relax-and-fix, aggregation, matheuristics, or heuristics when exact methods were impractical
• Experience running optimization workloads in production environments—handling timeouts, cancellations, and parallel execution
• Strong Python for production systems: testing, typing, code review, profiling before tuning. You understand numerical issues at the model-solver boundary (scaling, tolerances, integrality constraints)
• Genuine interest in customer problems and data quality, not just mathematical elegance
• Team collaboration experience
• German language proficiency at C1 or higher; fluent English
• Based in or willing to work hybrid from North Rhine-Westphalia (Cologne area), Munich, Stuttgart, or Berlin

Nice to have:

• Solver internals knowledge
• Performance optimization on numerical or compiled code
• DSL or compiler development
• Domain expertise in production planning, supply chain, or logistics

You should be: structured, action-oriented, and comfortable owning outcomes rather than waiting for tasks to be assigned.

This role is not a fit if you: prioritize research freedom over product delivery, prefer abstraction over hands-on data work, want to rewrite systems before measuring them, or need a structured task queue to stay productive.

How We Work With You

Candidates apply directly through Get A Job.ai. Our recruiting team will conduct an initial screen, then coordinate interviews with the client's technical leadership and optimization team. The process typically includes a technical discussion, a hands-on modeling challenge (approximately three hours) with a solution walkthrough, and final conversations with the team both remotely and in person.

Expected timeline is two to three weeks end-to-end, with feedback within days after each stage. Do not contact the client directly—all communication flows through our talent team to ensure a structured, confidential process.

Pay

Compensation details including salary range and equity participation will be discussed during the screening process and are competitive for senior optimization engineering roles in the German market.

Get A Job.ai is an equal opportunity recruiter. We work with clients and candidates without regard to race, color, religion, sex, national origin, age, disability, or any other protected characteristic. We are committed to building diverse teams and inclusive workplaces.