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Job Summary
We are seeking a talented Simulation Engineer to join our team, specializing in Digital Twin Simulation and Network Optimization. This role involves designing and implementing simulation models and optimization solutions to enhance warehouse logistics, resource allocation, and network efficiency. The ideal candidate will bring strong technical expertise in Python, simulation modeling, and optimization techniques, along with a passion for solving complex operational challenges.
Responsibilities
- Develop and maintain digital twin simulations for warehouse and logistics systems, modeling system states, events, and resource interactions.
- Create and optimize network models to improve flow, resource allocation, and operational performance.
- Collaborate with stakeholders to integrate simulation and optimization solutions into existing workflows.
- Analyze simulation outputs to pinpoint inefficiencies and recommend actionable improvements.
- Write modular, testable, and efficient code to support simulation and optimization projects.
- Document processes, methodologies, and findings for technical and non-technical audiences.
Must-Have Technical Skills
- Core Python: OOP, data structures, algorithms; writing modular, testable, efficient code
- Data Manipulation & Numerical Computing: pandas for cleaning/analysis; NumPy for computations
- Data Ingestion: fetching from REST APIs (requests) and databases (SQL)
- Discrete-Event Simulation: DES principles; SimPy for modeling states, events, resources (e.g. warehouse flows)
- Operations Research & Optimization: LP/MIP formulation; Python libraries (OR-Tools, Pyomo, PuLP); familiarity with VRP basics and assignment problems
- Graph Analytics: NetworkX for building/analyzing network topologies and flows
- DevOps & Version Control: Git with CI/CD pipelines; Docker containerization
- API Development: building/deploying REST services with Flask or FastAPI
- Visualization: creating plots and dashboards using Matplotlib, Seaborn, or Plotly
Nice-to-Have Technical Skills
- Advanced Routing & Heuristics: VRP variants (time windows, Hours of Service); heuristics/meta-heuristics (Tabu Search, Genetic Algorithms, Branch & Bound, Simulated Annealing)
- Commercial Solvers: Gurobi or CPLEX and their Python APIs
- ML-Enhanced Simulations: integrating scikit-learn or TensorFlow/PyTorch models for predictive maintenance or anomaly detection in digital twins
- Alternative Simulation Paradigms: agent-based modeling, etc.
- Streaming & IoT: real-time data processing with kafka-python; MQTT (paho-mqtt) for live twin updates
- Geospatial Processing & Visualization: GeoPandas, Shapely; routing engines/APIs (OSRM, Google Maps, HERE); Folium for maps
- Interactive Dashboards: Dash or Streamlit
- 3D Visualization: pyvista or vedo for complex digital-twin renderings
Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements.
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