Job Summary

Senior AI/ML Scientist(IC) (Operations Research/Optimization)

As part of the APM Terminals technical team, you will have a leading role in designing, building, maintaining, and iterating on products that directly impact terminal operations.

This position offers opportunities to develop and apply your deep knowledge of operations research methods to create operational and strategic insights transforming container terminal operations globally.

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 current 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.

📌 Senior Operations Research Engineer (Bengaluru)
🏢 A.P. Moller - Maersk
📍 Bengaluru