Senior Operations Research Engineer

This is a fully remote position, open to applicants in Poland.

📋 Description

• Create and execute mathematical optimization models for intricate industrial challenges.

• Formulate algorithms for planning, scheduling, routing, allocation, and decision-making support.

• Partner with machine learning engineers to integrate optimization strategies with AI solutions.

• Develop scalable optimization pipelines utilizing Python and contemporary software engineering methodologies.

• Authenticate optimization models via simulation and experimental validation.

• Evaluate algorithm performance and consistently enhance solution quality and computational effectiveness.

• Collaborate with cross-functional teams to grasp business goals and convert them into mathematical frameworks.

• Record methodologies, assumptions, and experimental findings for knowledge dissemination and future advancements.

• Tackle intricate optimization challenges at scale for a global technology firm dedicated to AI-centric industrial solutions.

• Transform business obstacles into scalable optimization solutions appropriate for production settings.

⛳️ Requirements

• MSc or PhD in Operations Research, Applied Mathematics, Industrial Engineering, Computer Science, or another STEM field.

• In-depth understanding of linear programming, mixed-integer programming, constraint programming, nonlinear optimization, or heuristic/metaheuristic algorithms.

• Proven ability to convert business issues into mathematical optimization frameworks.

• Proficient in Python programming.

• Experience in developing production-quality software, rather than merely research prototypes.

• Familiarity with large datasets and the creation of efficient optimization workflows.

• Strong analytical reasoning and problem-solving abilities.

• Capability to work autonomously in a research and development environment with changing requirements.

• Effective communication skills.

• Proficient in English.

• Nice-to-have: experience with machine learning or AI-enhanced optimization.

• Nice-to-have: background in simulation, stochastic optimization, agent-based modeling, or Markov models.

• Nice-to-have: understanding of high-performance computing (HPC).

• Nice-to-have: familiarity with cloud platforms and distributed computing.

• Nice-to-have: experience with industrial optimization scenarios such as logistics, manufacturing, energy, robotics, or supply chain.

🏝️ Benefits

• Equal opportunities in recruitment, career progression, and leadership roles.

• A diverse and inclusive workplace culture.

• Support from the talent team throughout the recruitment process.

• Technical interviews designed without trick questions.

• A warm welcome and assistance from the new team.