Senior Operations Research Engineer (AI)

Location: Fully remote within Poland or other EU countries

Company

Global technology services provider delivering AI-driven industrial solutions, enterprise technology, product development, and software engineering services.

What you will do

• Design and implement mathematical optimization models for complex industrial problems.
• Develop algorithms for planning, scheduling, routing, allocation, and decision support.
• Build scalable optimization pipelines in Python using modern software engineering practices.
• Collaborate with software engineers, data scientists, and machine learning specialists to integrate optimization with AI solutions.
• Validate models through simulation and experimentation while analyzing algorithm performance.
• Document assumptions, approaches, and experimental results for knowledge sharing and future development.

Requirements

• MSc or PhD in Operations Research, Applied Mathematics, Industrial Engineering, Computer Science, or another STEM discipline.
• Strong knowledge of linear programming, mixed-integer programming, constraint programming, nonlinear optimization, or heuristic and metaheuristic algorithms.
• Experience translating business problems into mathematical optimization models.
• Strong Python skills and experience building production-quality software.
• Experience with large datasets and efficient optimization workflows.
• Strong analytical, problem-solving, communication, and independent working skills; fluent English required.

Nice to have

• Experience with machine learning or AI-assisted optimization.
• Knowledge of simulation, stochastic optimization, agent-based modeling, or Markov models.
• Experience with high-performance computing, cloud platforms, or distributed computing.
• Experience solving optimization problems in logistics, manufacturing, energy, robotics, or supply chain.

Culture & Benefits

• Fully remote work within Poland or other EU countries.
• Research-driven environment where ideas can become production systems.
• Collaboration across software engineering, data science, and machine learning disciplines.
• Equal-opportunity workplace focused on inclusion, respect, and professional growth.

Hiring process

• Application review followed by a Talent Acquisition interview.
• Technical interview focused on expertise, problem-solving, and engineering approach.
• Customer interview may follow, then a job offer and onboarding.