Machine Learning Engineer

Job description As a Machine Learning Engineer at KPN, you translate advanced analytics and AI models into reliable, scalable solutions that have measurable impact for KPN. You work at the intersection of data science and software engineering: you take ideas from exploration to production and continuously improve them once they are live. We will only consider candidates already residing in the Netherlands. You work in multidisciplinary teams with data scientists, ML engineers, software and data engineers, network specialists, architects and business stakeholders. Together, you translate complex operational challenges into robust AI products and capabilities. - Designing, building and maintaining end-to-end machine learning solutions: from problem definition and experiment to deployment and lifecycle management. - Developing clean, testable and maintainable production code, APIs, data and ML pipelines, and reusable components. - Operationalizing models and analytical capabilities by integrating them into business processes, IT landscapes and data platforms. - Determining the solution architecture and infrastructure together with engineers, domain experts and enterprise or domain architects. - Applying DevOps and MLOps principles, including automated testing, CI/CD, observability, monitoring, feedback loops and responsibility for production. - Improving the reliability, scalability, robustness and performance of existing AI solutions and pipelines. - Exploring new AI methods and engineering practices and actively sharing knowledge within the team and KPN's broader AI community. You will join the AI for TDO team, part of the AI Excellence Center: an international, multidisciplinary environment focused on applying data and AI within KPN's network and operations. The team combines expertise in machine learning, mathematics, data engineering, software engineering and telecom domains. We value curiosity, pragmatic innovation, knowledge sharing and constructive debate. You will have the space to shape solutions, learn from experienced specialists and contribute to KPN's ambition to become more AI-native and work toward autonomous operations. You are analytically strong and move easily between a business problem, a model and the software system around it. You take responsibility beyond the prototype, communicate clearly with technical and non-technical colleagues, and find it interesting to delve into the complexity of telecom networks. You make well-considered engineering choices and know when to experiment, standardize or simplify. - A completed master's degree, or comparable work and thinking level, in Artificial Intelligence, Computer Science, mathematics, econometrics, applied physics or a related discipline. - Extensive experience in machine learning engineering, software engineering or data science, including building production-ready solutions. - Strong Python skills and experience with Git, automated testing, APIs, containers and CI/CD. - Knowledge of end-to-end ML systems, including data pipelines, model serving, monitoring, lifecycle management and feedback loops. - Experience with cloud-native architectures and scalable services; experience with Azure, AWS, Kubernetes, Dataiku DSS or ETL tooling. - Excellent communication skills in English; command of Dutch and experience in the telecom sector are a plus. Of course, as an employer we also have a lot to offer you. Here is what you get from us: - A gross monthly salary of at least € 5,216 and at most € 7,843 depending on your work experience, based on 40 hours. - A fixed 13th month: part of it is paid monthly and part in January of the following year. Or you can invest it in a FLEX & BOOST goal of your choice! Click here to read more about it. - Annual individual and collective salary increase in line with our CAO. - € 1,500 per year in employability budget that you may use at your own discretion, for example for training, coaching and courses. - Flexible days off: our colleagues may decide for themselves (in consultation with their manager) how they handle leave. - A good work-life balance (such as 2 days in the office, 3 days at home, transition leave, and holiday swapping to a holiday of your religious or cultural preference). - A home workspace allowance to set up your workspace at home optimally, including a mobile phone and laptop. - 50% discount on our products and services, so you can internet, call and stream affordably. - Good travel allowance: your public transport costs are fully reimbursed, or € 0.23 per kilometer if you travel by car. Prefer to cycle? Then you can claim our bicycle allowance of € 0.40 per kilometer. - Option to purchase a lease bike to which KPN contributes monthly (with an indefinite-term contract): from city bike to e-bike and from racing bike to speed pedelec; you choose what you ride. - Excellent pension conditions: a total contribution of 25% of your pensionable salary, of which KPN contributes 17.5% and you contribute 7.5%. Our belief in technology is strong. It becomes even more powerful together with human contact, which is why we would love to meet you!