MLOps Engineer

You own the path from trained model to reliable deploying it in production. As MLOps Engineer on our Vision Solution Platform, you make sure computer vision models run smoothly, scale confidently, and improve continuously across PostNL's logistics network.

Why you choose PostNL as a MLOps Engineer

Visible impact : Your work directly improves logistics operations you can see in every street in the Netherlands. Tracking roll containers, detecting anomalies, and turning camera feeds and images into actionable insights.

Real ML challenges : You work with production computer vision models at scale. Think video streams, object detection, model drift, and continuous retraining.

Greenfield opportunity : The platform is growing from a few depots toward all our depots. You help us shape the MLOps foundations from the ground up.

Great team culture: A small, collaborative team that is focused on knowledge sharing, troubleshoots together, and values pragmatic solutions over perfection.

Flexibility : Work from home, from our office in The Hague, or occasionally on-site at logistics locations. The team is always in-office on Tuesdays and sometimes Thursdays.

Growth : Develop yourself via the PostNL Academy and grow alongside a platform that's scaling fast.

Your role

Our Vision Solution Platform turns camera footage and images from logistics locations into reliable operational insights. As an MLOps Engineer, you make sure our computer vision models move smoothly from development to production. You build and maintain ML pipelines, automate model validation, and manage model versioning and deployments. Your work helps improve processes such as counting roll containers, recognising parcel stickers, and detecting operational exceptions. This allows our logistics teams to work smarter and make better decisions every day.

You work closely with ML Engineers, AWS Engineers, and other specialists to keep models reliable, scalable, and easy to maintain. You monitor model performance, detect data and model drift, and help improve the platform as it expands to more locations across the Netherlands. At the same time, you contribute to technical decisions, CI/CD improvements, and the future development of our AI and computer vision platform.

Your team

You'll join the Vision Solution Platform team, which is a small, growing team of roughly five to six people including a product owner, ML/AWS engineers, and a solution consultant. The team has a strong R&D mentality and operates at the frontier of what's possible within our organization. We solve problems together, with short feedback loops and a shared sense of ownership.

What we deliver

A role full of innovation and work that you can literally see in every street in the Netherlands. At us, we want to become the logistics e-commerce platform of the future. This helps us deliver special moments even smarter, faster, and better. Your mindset and our ambition. Together, we make it happen. In return, you can count on an attractive package of employment benefits.

The top benefits of your role are:

• A salary between €4,092 and €6,499 gross per month based on 37 hours per week. Working 32 hours per week is also possible.
• The freedom to work hybrid and organise your working hours flexibly. If you work from home two or more days per week, you receive a net home office allowance of €45 per month.
• 8% holiday allowance and 25 vacation days when working full-time.
• Travel allowance for commuting, including an NS Business Card or kilometre reimbursement.
• A good pension scheme through the PostNL pension fund.
• An engineering laptop (Mac or Windows) and smartphone.
• Learning and development opportunities through the PostNL Academy.
• Discounts on holidays, events, and products.

What you bring

You are a hands-on MLOps Engineer who enjoys taking ownership and building structure in an environment that is still evolving. You communicate clearly, work well with different disciplines, and help turn innovative ideas into reliable solutions. Experience with computer vision, AWS, image and video data, or edge deployments helps you get up to speed quickly, but your willingness to learn and improve is just as important.

You recognise yourself also in the following:

• You have at least 3 years of experience in MLOps, ML Engineering, or a related role.
• You have strong Python and/or TypeScript skills.
• You have experience building and maintaining ML pipelines.
• You have experience with model deployment, model registries, and versioning.
• You have experience with CI/CD, Docker, and Kubernete