Senior Operations Research Engineer

A.P. Moller - Maersk A.P. Moller – Maersk is the global leader in container shipping services. The business operates in 130 countries and employs 80,000 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 optimization algorithms, simulation models 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.

Your Impact

You will be part of the APM Terminals technical team. As a Senior Operations Research Engineer, 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 operations research methods 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

Lead the design, implementation and delivery of advanced 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.

Coach and mentor junior team members in optimization techniques and operations research methodologies.

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.

Validate and iterate on optimization solutions against discrete event simulation models of terminal operations,

System design, architecture, and solution design for new features.

What you bring:

5+ years of industry experience in building and delivering optimization solutions

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).

Depth in optimization modelling — LP, MILP, constraint programming, and/or metaheuristics, applied to problems like scheduling, sequencing, routing, bin packing, and resource allocation.

Fluency implementing these in Python across open-source and commercial solvers (e.g. PuLP, OR-Tools/CP-SAT, HiGHS, Gurobi).

Experience developing optimization models for stochastic operational environments, and evaluating them against simulation.

Track record of delivering production-quality Python.

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

Experience in leading technical work, coaching junior colleagues, and driving projects from concept to delivery.

A strong plus:

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 operations. Experience in material handling, manufacturing operations, or other domains involving physical asset optimization and sequencing problems.

Discrete Event Simulation, AI/ML methods for operational problems, Prescriptive analytics (e.g., stochastic optimization, reinforcement learning).

Experience developing and interacting with generative AI models.

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.

We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing accommodationrequests@maersk.com .