AI/ML Scientist (Applied Scientist)

Job description

Data AI/ML (Artificial Intelligence and Machine Learning) Engineering involves the use of algorithms and statistical models to enable systems to analyze data, learn patterns, and make data-driven predictions or decisions without explicit human programming. AI/ML applications leverage vast amounts of data to identify insights, automate processes, and solve complex problems across a wide range of fields, including healthcare, finance, e-commerce, and more. AI/ML processes transform raw data into actionable intelligence, enabling automation, predictive analytics, and intelligent solutions. Data AI/ML combines advanced statistical modeling, computational power, and data engineering to build intelligent systems that can learn, adapt, and automate decisions. A.P. Moller - MaerskA.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: You will join a technical team of around 50 people in APM Terminals, building the systems behind some of the world's leading container terminals — where the cranes move, the yard fills up, and the vessel is waiting.  What makes this work inspiring is how close it sits to the operation. Your models are not evaluated in isolation: they are discussed with the people who run the terminal and measured against what actually happens there. Getting that right is demanding, and it is what makes the results worth something.  Our backgrounds span operations research, simulation, machine learning, software engineering, and terminal operations themselves. Nobody here covers all of it, and that is deliberate — the most interesting problems tend to sit between two people's expertise.    Your Impact  You will be part of the APM Terminals technical team. As an Applied Scientist, you will have a key role in designing, building, maintaining, and iterating on data-driven products that directly impact terminal operations. This position offers a unique opportunity to apply your technical knowledge 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.    Key Responsibilities  • Design, implement and deliver advanced solutions for terminal operations including container handling equipment efficiency, yard positioning strategies, vessel loading/unloading sequencing, and vehicle routing — contributing to system design, architecture, and solution design as new features take shape.  • Build both operational tools for real-time, day-to-day terminal operations and strategic models for long-term planning and decision-making.  • Act as the bridge between the physical yard and the code, translating messy, stochastic physical realities into logical mathematical models.  • Explain complex model rationale and results to non-technical terminal operators and leadership to build trust and successfully roll out solutions to production environments.  • Monitor model performance against actual physical terminal events, iteratively improving models to handle operational drift and increase effectiveness.    What You Bring (The “T-Shaped” Profile)  We are looking for hybrid problem-solvers. We do not expect you to know everything; rather, we want to see a solid technical foundation combined with real depth somewhere.    The Core Foundation (Required)  • Experience: We typically look for 5+ years of industry experience building and delivering technical or optimization solutions. This is a guideline, not a filter — a strong PhD, or exceptional demonstrated ability, can substitute for part of it. We do expect some industry experience: you should have shipped something real that people depend on.  • Education: M.Sc. or PhD in Operations Research, Industrial Engineering, Machine Learning, Statistics, Applied Mathematics, Computer Science, or a relat