
Machine Learning Engineer | Groningen
Research and Develop software solutions that shape autonomous systems in energy transition, defence, and smart industry. Work on high-impact applications with real-world challenges Become a Machine Learning Engineer at TNO in Groningen
About this position
AI is transforming industries, but in critical environments, it must be reliable, scalable, and secure. At TNO, we develop AI-driven systems that interact with physical processes (sensors, actuators), and make autonomous decisions in complex, real-world scenarios—from adaptive energy grids and defence intelligence networks to biodiversity digital twins that support environmental policy. As a Machine Learning Engineer, you will contribute to the research, development, and implementation of machine learning solutions that directly impact vital infrastructure. You will work with leading experts in AI, distributed systems, and software engineering to develop innovative applications that bridge the gap between fundamental research and practical deployment. Aspects such as assessing and improving system performance, safety, and controllability will be part of your work. The research group Intelligent Cyber-physical Systems Engineering (ICSE) is your home base. From Groningen and The Hague, more than 35 scientists, researchers, and consultants prove the added value of digital applications every day. You’ll also work closely with colleagues from other departments and units. ICSE is a great mix of highly qualified women and men with different levels of experience and of various nationalities. We all have a passion for applied research and we enjoy talking about it in an open and informal atmosphere we’re there for each other, support each other, and are open to your ideas!
What will be your role?
As a Machine Learning Engineer, you will be involved in the full lifecycle of Machine Learning solutions, from research and experimentation to building and deploying robust Machine Learning models and AI-based systems. Your role includes:
- Developing Machine Learning software that enhances autonomy in cyber-physical systems.
- Building proof-of-concept applications and demonstrators that translate AI research into practical, scalable solutions.
- Optimizing and deploying Machine learning models, ensuring performance, reliability, and efficiency.
- Collaborating with multidisciplinary teams, including experts in AI, systems engineering, and domain-specific applications.
- Exploring cutting-edge AI techniques and evaluating their real-world applicability in critical infrastructure and in when interacting with physical processes.
- Work with customers and partners to solve new and existing problems using state-of-the-art Machine Learning technology.
Examples of currently running projects:
- AI Agents for Military Intelligence – Developing generative AI agents that assist analysts in filtering large-scale data for actionable insights.
- GPT-NL [https://gpt-nl.nl/] – Contributing to data curation and training pipelines for the first large-scale, lawful Dutch AI language model.
- Sustainable (re)manufacturing – AI-based decision support for optimizing handling of returned products.
What we expect from you
You are an ambitious Machine Learning Engineer with a strong technical foundation and a passion for applying AI to real-world challenges. You have a passion for building reliable, safe, and performant digital products, and an open mind to work on a cross-expertise environment.
Other knowledge and skills you bring to TNO:
- A PhD or master’s degree in Computer Science, Artificial Intelligence, or a related field.
- Strong collaboration and communication skills to work in multidisciplinary teams. A pro-active and independent work attitude.
- Experience with Python, and a willingness to learn new programming languages and platforms like Rust, TypeScript, Java or Go. Knowledge of and preferably experience with machine learning frameworks such as PyTorch or TensorFlow.
- An analytical mindset and curiosity to explore new AI techniques on the one hand, while keeping a critical and pragmatic perspective on the impact of AI on the other hand.
And one or more of the following:
- A understanding of software engineering principles, including MLOps, and DevOps. Experience with design and integration of distributed systems, monitoring, and data-processing systems.A mathematical background on modelling (e.g. physical processes) and implementing these models in code.
- An intrinsic interest in engineering phases such as design, validation and verification, lifecycle management, and system assessment. Preferably, experience with conceptual modelling techniques such as UML or SysML.
What you'll get in return
Challenging and varied work with a real impact. And plenty of opportunities as, at TNO, you are in charge of shaping your career. We offer a gross monthly salary between € 3,385 and € 5,000 (based on your knowledge and experience), 8% holiday pay, a 13th month bonus of 8.33% and a flex budget (5.58% + € 180). In addition, you will be given every opportunity to develop yourself.
Perhaps you would like to grow your career in the direction of commerce or consultancy? Or would you like to become a project manager? Immerse yourself in sustainable innovations? Or carve out a career as a technical expert?
- TNO offers optional employee benefits, enabling you to tailor your benefits package to match your personal situation. You may also expect:
- An extremely professional, innovative working environment where colleagues are leading experts in their field.
- The opportunity to attend courses, workshops and conferences, and to receive training and coaching based on your needs.
- 33 days annual leave on a full-time basis.
- An employer that values and encourages diverse talent, with initiatives like the Female Leadership Program, our Rainbow Community and round tables on inclusion topics.
- We offer a comprehensive and flexible mobility plan that also includes full compensation for public transportation for commuting and business travel.
- Great social events with your team and other TNO colleagues. That’s how you will get to know a lot of people really quickly.
- Flexible working hours, the possibility to work parttime (32 of 36 hours) and the possibility of working from home.
- A good pension scheme.
Read more about tailoring your benefits package.
TNO as an employer
At TNO, we innovate for a healthier, safer and more sustainable life. And for a strong economy. Since 1932, we have been making knowledge and technology available for the common good. We find each other in wonder and ingenuity. We are driven to push boundaries. There is all the space and support for your talent and ambition. You work with people who will challenge you: who inspire you and want to learn from you. Our state-of-the-art facilities are there to realize your vision. What you do at TNO matters: impact makes the difference. Because with every innovation you contribute to tomorrow’s world. Read more about TNO as an employer.
At TNO we encourage an inclusive work environment, where you can be yourself. Whatever your story and whatever unique qualities you bring to the table. It is by combining our unique strengths and perspectives that we are able to develop innovations that make a real difference in society. Want to know more? Read what steps we are taking in the area of diversity, equity and inclusion.
The selection process
Please apply before the 7th of September, 2025. The selection process comprises two interview rounds. The preliminary interview takes place on the 18th of September, 2025. The second interview round has been scheduled for the 22nd of September, 2025. In a final meeting we will discuss the terms of employment and your tailored benefits package. We aim to finalize the entire process within four weeks.
The selection process may include an online assessment and a reference check.
A certificate of Conduct (VOG) is required before starting a new job at TNO.
Has this job opening sparked your interest?
Then we’d like to hear from you! Please contact us for more information about the job or the selection process. To apply, please upload your CV and covering letter using the ‘apply now’ button.
More information about this vacancy?
Posted by: #LI-YP1 Yvonne Pribnow
Email: [email protected]