intro

Through your Machine Learning solutions, you create simplified processes for our customers and help us establish ourselves as 'digital first'.
With a solution-oriented and active mindset, you come up with technical solutions, using AI models. Through your solutions, the data team and the AI team create more business value. In addition to creating business value, knowledge transfer and coaching are also an important part of your job. The goal is to take the engineering skills of your fellow data scientists to the next level, among other things by following best practices.

Wat ga je doen?

You are able to take the lead in devising and designing AI-driven applications. We are currently mainly building state-of-the-art applications with (OpenAI's GPT) LLMs. An important point of attention here is that everything is secure, scalable and repeatable. You will work closely with the Data Scientists to improve the Machine Learning Lifecycle. The focus is on code quality, CI/CD, testing and monitoring. Security is an important part of your application and you are aware of the compliance rules within NN. If you would love to experience an overlap of AI, Software and Data Engineering in your work, then this is your place.

You bring AI models (data products) to production, for example in the form of APIs
You develop and maintain the machine learning infrastructure, fitting into the NN landscape
You develop AI applications based on CI/CD, high-quality code, testing and monitoring

Wat wij jou bieden

NN invests in an inclusive, inspiring work environment and in skills and competences for the future. We match this with employee benefits that are in line with what is needed today and in the future. This way, we offer our employees the opportunity to get the best out of themselves. We offer you:

Salary between €3.973 and €5.675 depending on your knowledge and experience
13th month and holiday allowance are paid with your monthly salary
27 vacation days for a 5-day working week and one Diversity Day
A modern pension administered by BeFrank
Plenty of training and learning opportunities
NS Business Card 2nd class, which gives you unlimited travel, also privately. Do you prefer to travel with your own transport? Then you can declare the kilometers travelled
Allowances for setting up your home office and for internet use

We work hybrid at NN. Together with your team, you decide where, how and when you work. The official location of this job is The Hague.

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Wat je meebrengt

You find it important to bring well-designed applications to production with low maintenance. Furthermore, you enjoy sharing your knowledge with others. You like to take the time to take your colleagues along in your steps and explain things to them. Your open attitude and strong communication skills help enormously with this. Furthermore, you have:

A bachelor's or master's degree in IT or a study with a strong IT component, with at least 3 years of work experience
Experience in the field of Software/DevOps engineering and developing ML applications
Working knowledge of the data science process, such as data collection, cleaning, model review, and model implementation
Experience in developing (Flask) APIs and CI/CD
Preferably experience with building applications in the (Azure) Cloud, Docker & Kubernetes
We are looking for a candidate who is fluent in both English and Dutch

Met wie je werkt

You will be working in our Competence Center, where we work on applications for the business through projects. Your team includes several data scientists and a Machine Learning OPS Engineer. You will work closely with your fellow Machine Learning OPS Engineer. We also work with various end-to-end teams, all of which exchange specialist knowledge. In this way, we work very efficiently on scalable solutions. In this process, we learn a lot from each other. Our ambition is to become even better at AI.

Together we work on state-of-the-art solutions, in Python and in the (Azure) cloud. In your work, you experience a lot of freedom and responsibility. That ensures that you continue to grow. In the team we work hybrid, where we meet together at the office at least once a week.