AI/ML Scientist

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.

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 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.

• 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.

• Build both operational tools for day-to-day terminal operations and strategic models for long-term planning and decision-making.

• Collaborate and communicate model rationale, results and insights with product teams, leadership and business stakeholders to roll out solutions to production environments.

• PhD or M.Sc. in Operations Research, Industrial Engineering, Machine Learning, Statistics, Applied Mathematics, Computer Science, or other field related to algorithms and data (or equivalent experience).

• 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.

• Ability to understand complex operational systems and translate business requirements into effective technical solutions.

• Experience working with cloud environments.

• Experience in container terminal operations, port logistics, or similar operational environments with complex resource allocation and scheduling dynamics.

• Experience developing and interacting with generative AI models.