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.

AI/ML Scientist (Operations research / Optimization / Simulation)

We are now seeking a new team member who is excited about developing advanced simulation models, optimization algorithms 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.

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.

Key Responsibilities

- 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.
- Develop and maintain productive applied engineering solutions that solve real-world operational challenges at container terminals globally.




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

To do this job, we imagine you have:

- 5+ years of industry experience in building and delivering simulation models, optimization solutions, or data science products.
- 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).
- Strong experience in simulation modeling and optimization, particularly in operational environments with complex dynamics.
- 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.
- Excellent record of delivery using Python and technologies like Git, JIRA, etc.
- Ability to understand complex operational systems and translate business requirements into effective technical solutions.
- Strong communication skills with ability to work independently with stakeholders while liaising and reviewing with the team.
- Experience working with cloud environments.

Nice to have:

- 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.
- Experience developing and interacting with generative AI models.

CORE SKILLS Data Analysis: The process of inspecting, cleansing, transforming, and modeling data to discover useful information, draw conclusions, and support decision-making Proficiency Level: Proficient

Statistical Analysis: The process of collecting and analyzing data to identify patterns and trends, and to make informed decisions. Proficiency Level: Proficient

AI Machine Learning: The field of artificial intelligence (AI) involves creating systems that can perform tasks that typically require human intelligence. Machine learning (ML) is a subset of AI that uses algorithms to learn from and make predictions based on data Proficiency Level: Proficient

Programming: Writing

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 AI/ML Scientist(Operations Research) (Karnataka)
🏢 APM Terminals
📍 Karnataka