AIML Scientist(Operations researchOptimizationSimulation)

AI/ML Scientist (Operations research/Optimization/Simulation)

A.P. Moller - Maersk

A.P. Moller Maersk is the global leader in container shipping services. The business operates in 130 countries and employs 80000 staff. An integrated container logistics company Maersk aims to connect and simplify its customers supply chains.

Today we have more than 180 nationalities represented in our workforce across 131 Countries and this mean we have elevated level of responsibility to continue to build inclusive workforce that is truly representative of our customers and their customers and our vendor partners too.

The team - who are we:

We are an ambitious team with the shared passion to use data data science (DS) machine learning (ML) advanced simulation optimization and engineering excellence to make a difference for our customers.

We are a team not a collection of individuals. We value our diverse backgrounds our different personalities and strengths & weaknesses. We value trust and passionate debates. We challenge each other and hold each other accountable. We uphold a caring feedback culture to help each other grow professionally and personally.

We are now seeking a new team member who is excited about developing advanced simulation modelsoptimization algorithms and AI/ML solutions that create operational insights for container shipping terminals

worldwide helping them optimize container handling yard operations vessel operations and drive efficiency

and business value.

We Offer - This Is What You Get

You will be part of the APM Terminals team within Global data and analytics (GDA) responsible for developing and delivering advanced simulation models optimizations and AI/ML models for container shipping

terminals. As an AI/ML Scientist you will have a leading role in designing building maintaining and

iterating on products that directly impact terminal operations.

This position offers a unique opportunity to develop and apply your deep knowledge of simulation optimization data science methods software engineering and modern AI development tools to create

operational and strategic insights that are transforming container terminal operations globally.
This is an exciting time to join a growing and dynamic team that solves some of the toughest problems in

terminal operations and builds the future of container shipping. We offer a unique opportunity to impact global trade via world-leading container terminals. We focus on our people and the right candidate will have broad

possibilities to further develop competencies in an environment characterized by change and continuous Progress.

Key Responsibilities

• Design implement and deliver advanced simulation models and optimization solutions for terminal operations including container handling equipment efficiency yard positioning strategies vessel loading/unloading sequencing and truck routing.
• Develop and maintain efficient applied engineering solutions that solve real-world operational challenges at container terminals globally.
• Build both operational tools for day-to-day terminal operations and strategic models for long-term planning and decision-making.
• Work with relevant stakeholders to understand terminal operational dynamics and business processes incorporating their needs into products to enhance value delivery.
• Collaborate and communicate model rationale results and insights with product teams leadership and business stakeholders to roll out solutions to production environments.
• Analyse data measure delivered value and continuously evaluate and improve models to increase effectiveness and operational impact.

To do this job we imagine you have:

• 5 years of industry experience in building and delivering simulation models optimization solutions or data science products.
• PhD Operations Research Industrial Engineering Machine Learning Statistics Applied Mathematics Computer Science or other field related to algorithms and data (or equivalent experience).
• Strong experience in simulation modeling and optimization particularly in operational environments with complex dynamics.
• Research or industry experience in one or more: Discrete event simulation Combinatorial optimization problems (e.g. scheduling vehicle routing bin packing sequencing) Continuous optimization problems (e.g. linear programming mixed-integer programming convex programming) AI/ML methods for operational problems Prescriptive analytics (e.g. stochastic optimization reinforcement learning).
• Experience with AI development tools and code assistants (GitHub Copilot Cursor Claude Code or similar) for enhanced productivity.
• Excellent record of delivery using Python and technologies like Git JIRA etc.
• Ability to understand complex operational systems and translate business requirements into effective technical solutions.
• Strong communication skills with ability to work independently with stakeholders while liaising and reviewing with the team.
• Experience working with cloud environments.

Nice to have:

• Experience in container terminal operations port logistics or similar operational environments with complex resource allocation and scheduling dynamics.
• Familiarity with container handling equipment yard operations or vessel operationsExperience in material handling manufacturing operations or other domains involving physical asset optimization and sequencing problems.
• Experience developing and interacting with generative AI models.