Key Skills

Job Description

What is the opportunity and why should you apply? What: Lead an engineering squad building APMT's Operations Intelligence capability. You will own delivery of AI-powered digital twins, integrated planning systems and operations research models across vessel, yard, gate and rail workflows. You will be hands-on in architecture and code reviews, grow a high-performing team, and turn the platform roadmap into production systems that move ROIC. Why: This platform unifies vessel, gate, yard and rail operations into one coordinated system that integrates with the Future Execution Platform. It closes the loop from planning to execution. When OR models and digital twins predict bottlenecks and remove waste before it hits operations, that is competitive separation, and your squad builds it. What You'll Build & Deliver Simplify Operations: Operations Research & Mathematical Optimization Build MILP, Constraint Programming and stochastic optimization models for berth scheduling, storage allocation and equipment routing, the mathematical backbone of the AI Big Bet Apply optimization to historical terminal designs to accelerate new terminal planning and shorten time-to-revenue Use DES to model operational continuity during expansion projects, as volume grows and construction constrains space Ship prescriptive solvers that produce executable plans and recommendations, not just predictions End-to-End Integrated Planning: Operational Digital Twin Extend the Discrete Event Simulation engine across vessel, gate, yard and rail to predict bottlenecks and test scenarios before they reach operations Build self-learning optimization engines for yard strategy, decking and container positioning Deliver integrated planning components that adjust in real time as vessels delay, volumes surge or equipment fails Build decision support tools that turn complex trade-offs into clear recommendations for operations teams APMT Business Systems: Deploy AI-powered process mining to find and remove waste from berth allocation to gate release Build continuous benchmarking that tests terminal performance against global best practice Deliver dashboards that connect frontline moves to financial outcomes Build predictive equipment utilization and labour optimization models so terminals serve more volume with the existing asset base Simplify Model Architecture: API-Driven Simulation & Agentic Capability Decompose monolithic simulation models into modular, API-accessible components that AI agents can call on demand Build agentic workflows that select and orchestrate simulation APIs based on operational questions, turning weeks of custom modelling into fast answers What Makes You Right For This Technical Foundation 10+ years in software or data engineering, including 3+ years leading engineers who ship AI/ML systems to production with measurable business impact Strong hands-on expertise in Python/R data science ecosystems, cloud infrastructure (AWS/Azure/GCP) and modern MLOps Practical experience with optimization (MILP/CP), simulation, predictive analytics or industrial IoT in logistics, manufacturing or infrastructure Credible enough technically to review designs, unblock engineers and make sound build decisions Business Mindset You understand how your team's work flows into ROIC through operational efficiency, commercial growth and concession wins You build reusable components, so each new DES or OR model strengthens the platform across the terminal network You translate operational realities into engineering requirements and explain technical trade-offs in terminal language Leadership You lead a squad of 6–10 engineers and data scientists, setting priorities, running delivery and holding a high quality bar under Engineering Excellence standards You coach and grow your engineers, hire well and build a team that ships, learns and improves You work closely with product owners, operations experts and peer squads to land integrated outcomes You turn a defined roadmap into crisp sprint plans and raise risks early Industry Fluency (Preferred) Background in ports, logistics, supply chain or asset-intensive operations Understanding of maritime operations, terminal economics or heavy industrial optimization Why This Role Matters Your squad's models and tools will help APMT win more business, run terminals more efficiently and compete on intelligence, not just scale. Every model you ship and every waste stream you remove flows directly to shareholder returns and better service for the supply chains. 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. 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Core Responsibilities

Lead a squad of engineers and data scientists delivering AI-powered digital twins, optimization models, integrated planning systems, and decision-support tools for vessel, yard, gate, and rail operations. Own technical architecture and delivery, develop reusable simulation and optimization capabilities, and align operational improvements with business outcomes.

Requirements

Requires 10+ years in software or data engineering, including at least 3 years leading engineers delivering production AI/ML systems with measurable business impact. Candidates should have hands-on expertise in Python or R, cloud infrastructure, MLOps, and optimization or simulation, plus the ability to lead a 6–10-person team and translate operational needs into engineering solutions.