We are looking for a ML Engineer who will help us solve valuable and complex business challenges for the Decision Intelligence team.

You will be part of a team alongside other Machine Learning Engineers, Data Scientists and Product Consultants within KLM Operations Decision Support (ODS) department. The core focus of ODS is to optimize processes concerning fleet, crew, ground services and the destination network. Our models aim to answer highly relevant questions such as:

how many meals are needed on board?; how much ground staff is needed and at what time?; how many no-shows can we expect on this flight?; how much delay will a flight incur and how can we minimize the impact?;

The answers to these questions directly influence the operations of KLM, which means plenty of opportunities to work on projects that truly save costs and/or increase robustness of the daily operations.

As a Machine Learning Engineer, you will turn machine learning solutions into reliable, scalable, and production-ready products. You will take ownership of the engineering aspects of projects, building robust, maintainable, and scalable solutions that deliver real business value.

We are expanding our Machine Learning capabilities and are looking for people who want to make an impact on KLM’s operations. Do you want to see the ML solutions you build in action the next time you take a flight? Then don’t hesitate to apply!

As a Machine Learning Engineer, you will work in the growing agile Decision Intelligence team. Together with other Machine Learning Engineers, Data Scientists, and Product Consultants, you will tackle challenging Machine Learning and GenAI projects whose outputs are used by more than five departments and directly support operations serving millions of KLM passengers.

Important aspects of your job on a day-to-day basis will be to:

• build ML solutions: develop and maintain ML solutions that are used in KLM’s operations. Your work can directly support operational processes such as meal planning, workforce planning, and flight operations;
• own the ML pipeline: design, develop, and maintain the end-to-end ML pipeline, from data preparation and model training to deployment, monitoring, retraining, and continuous improvement;
• productionize ML models: work closely with Data Scientists to turn models and prototypes into reliable, scalable, and production-ready solutions that can be integrated into KLM’s operational systems;
• ensure reliability and performance: continuously monitor production models and pipelines, identify issues and bottlenecks, and improve their reliability, performance, scalability, and maintainability;
• build and improve cloud infrastructure: design and implement scalable, reliable, and cost-efficient cloud infrastructure on Google Cloud Platform to support the development, deployment, and operation of ML solutions;
• develop and maintain data pipelines: ensure that the data pipelines supporting ML models are reliable, efficient, and fit for production use, working closely with Data Engineers where needed;
• apply strong software engineering practices: write clean and maintainable code and contribute to automated testing, version control, CI/CD, documentation, code reviews, and monitoring;
• work across disciplines: collaborate closely with Data Scientists, Data Engineers, Product Consultants, and other technical colleagues to bring ML solutions from development into production and ensure they meet operational needs;
• improve our way of working: identify opportunities for standardization, reuse, automation, and improvements to our tooling and processes;
• share knowledge and innovate: stay up to date with developments in Machine Learning, MLOps, cloud technologies, and AI. Experiment with new approaches and share your knowledge and lessons learned with colleagues, for example through our Data Science Community.

You are also encouraged and expected to spend 15–20% of your time learning new things, doing research and developing yourself. You can do this by following courses, reading papers or doing cool hack projects with your colleagues.

You’ll work within the department of Operations Decision Support (ODS), the data and analytics hub of KLM Operations. The Decision Intelligence team combines machine learning, generative AI and optimization to make operational decisions smarter and more predictable.

You will be part of a multidisciplinary team consisting of Data Scientists, Machine Learning Engineers and Product Consultants; combining talent with a drive for delivering results while having profound knowledge of the airline industry and KLM operations. 

You will be working in a hybrid way, partially from home and partially from the office (2 days) at Schiphol East, where you can watch the airplanes take off while your Docker container is being built.

You will be hired by the Data, OR & AI department, which will place you into one of the Data Science product teams in KLM. This department currently comprises about 40 Data Science professionals in product teams across KLM, sharing knowledge, training and (social) events.

We are looking for a motivated, enthusiastic, and proactive colleague with the necessary skills to solve the real business problems and provide value to KLM. You are comfortable taking ownership of complex problems and working with others to build reliable production solutions.

The skills and experience you bring to the team:

• a Master’s degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, or related fields;
• 2+ years of industry experience in Machine Learning Engineering, MLOps, or software development;
• experience developing and operating production Machine Learning systems, including model deployment, monitoring, retraining, and continuous improvement;
• strong experience with Python and writing clean, maintainable, testable, and production quality code;
• strong foundation in software engineering, including Object-Oriented Programming (OOP), design patterns, testing, code reviews, Git, and CI/CD;
• experience with Google Cloud Platform (GCP) and building scalable, reliable, and cost-efficient cloud-based ML solutions;
• experience with Docker, REST APIs, SQL, and infrastructure-as-code tools such as Terraform;
• experience working closely with Data Scientists and Data Engineers to productionize ML models and build reliable data and ML pipelines;
• experience with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG), including developing and deploying production-ready LLM/RAG applications is a plus;
• strong problem-solving and analytical skills, with the ability to translate complex business and technical requirements into practical engineering solutions;
• strong communication skills, with the ability to explain technical concepts clearly to both technical and non-technical colleagues;
• a curious and proactive mindset, with an interest in keeping up with developments in Machine Learning, MLOps, LLMs, RAG, and cloud technologies.

Flight Plan

Our selection process consists of three rounds and runs from 13 to 27 November 2026:

• intro call (one call on 13, 16 or 17 November): a first conversation about your motivation, your background and what you are looking for;
• technical assignment (one day at our office at Schiphol East, on 18, 19 or 24 November): a coding exercise and a system design discussion;
• final call (26 or 27 November): a conversation with the hiring manager and the team about fit and expectations.

• A challenging role with a unique employer in the Netherlandss;
• A gross monthly salary between € 4.348,98 and € 6.212,83;
• Plenty of room for personal development and great advancement opportunities;
• A good pension scheme;
• 8% holiday allowance;
• A year-end bonus of 8.33%;
• A profit-sharing scheme, up to 20%;
• 25 days of paid holiday and 5 additional days off;
• Great discounts on airline tickets (after at least 6 months of employment);
• A sustainable transport policy - use all public transport for your commute within the Netherlands, free of charge;
• If your job allows: working from home and up to 8 weeks working abroad (within the EU and Caribbean);
• Discount of your health insurance;
• A personal budget for sustainable employability.

Don’t wait any longer and apply for this function before the final boarding call on 11/11/2026! A motivation letter is no longer required; we will simply ask you a couple of questions during your online application. The selection process consists of two interviews and a security screening. Candidates who are positively selected for the first interview will receive an email allowing them to choose a suitable time slot themselves. This keeps the process fast and clear, and puts you in control of your schedule. You'll hear from us within two weeks after the vacancy closes.Through your personal candidate profile, you can log in at any time. There you'll find the vacancy you applied for - even after it has closed - as well as a clear dashboard with any other ongoing applications within KLM, including status updates.Do you have the drive to grow further in this role? Then we look forward to your application. Within two weeks, you will receive a message from us. Did you know that according to research, women are less likely to apply than men when they don't meet all the job requirements? What a shame. Because, in our view, 'the perfect candidate' is a myth. So, if you have the drive to grow in aspects of this role, we look forward to your application. A reference check can be part of the application procedure.