Senior AI/ML Engineer, Simulation

A.P. Moller - Maersk

full-time

Posted on: 9/20/2025

Origin: • 🇮🇳 India

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Senior

DockerFlaskIoTKafkaNumpyPandasPythonPyTorchScikit-LearnSQLTensorflow

About the role

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.
Design and implement simulation models and optimization solutions to enhance warehouse logistics, resource allocation, and network efficiency.
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.

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
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: Advanced Routing & Heuristics (VRP variants, heuristics/meta-heuristics)
Nice-to-Have: Commercial Solvers (Gurobi or CPLEX) and their Python APIs
Nice-to-Have: ML-Enhanced Simulations (scikit-learn or TensorFlow/PyTorch)
Nice-to-Have: Alternative simulation paradigms (agent-based modeling)
Nice-to-Have: Streaming & IoT: kafka-python; MQTT (paho-mqtt)
Nice-to-Have: Geospatial Processing & Visualization (GeoPandas, Shapely; routing engines/APIs; Folium)
Nice-to-Have: Interactive Dashboards (Dash or Streamlit)
Nice-to-Have: 3D Visualization (pyvista or vedo)
Ability to collaborate with stakeholders to integrate simulation and optimization solutions
Location: Hybrid in India (Bangalore or Pune)