ML/Cloud Engineer

You help build the Data Analytics Services based on a combination of AWS and open-source tools, ensuring that your colleagues can hunt for data wherever and whenever they want. With a few clicks, the PostNL data is gathered for data science and AI purposes, seamlessly fitting into the data experts' user experience and journey, while ensuring it is auditable, compliant, and secure.

That's why you'll choose PostNL as an AWS Cloud Engineer

Visible impact: Build a platform that virtualizes, operationalizes, and analyzes data. Your work will make the jobs of 50 data scientists and analysts more efficient and effective.

Challenge: Develop a self-service platform where data scientists can easily manage models and data. MLOps is still in its infancy here, giving you plenty of opportunities to make your mark.

Great atmosphere: Collaborate with a team that seizes opportunities and grows together. Innovation and humor are central to our culture.

Hybrid work environment: Combine working from home with a flexible workspace at our modern office in the historic Stationspostgebouw, next to Holland Spoor station.

Room for innovation: Experiment with the latest technologies during our quarterly innovation sprints. Beta programs such as AWS Bedrock and GitHub Next keep you at the forefront of innovation.

This is your role

As a Cloud Engineer, you will develop end-to-end Data Analytics Services and implement CDK-based AWS infrastructure focused on SageMaker. You will use TypeScript for infrastructure development and maintain a user-friendly SageMaker Python wrapper for data scientists.

Your work directly impacts our primary processes, ensuring stable, scalable, and innovative solutions with a keen focus on performance and cost. Leveraging your expertise in AWS Serverless, you will expand and mature the platform while addressing challenges related to adoption.

Your colleagues

You will join the Data Analytics Services team, an international group consisting of a Product Owner, Scrum Master, and six Engineers. Together, this team of passionate professionals develops efficient solutions while fostering a positive and supportive work environment. The team values learning, experimenting, and pushing boundaries.

This we deliver to you

A position full of innovation and work that you will see on every street in the Netherlands. At PostNL, we want to grow into the logistics e-commerce platform of the future. So that we deliver special moments even smarter, faster, and better. You can count on a great benefits package.

The top benefits of your position are:

• Salary between €3.971 and €5.472 gross per month (scale 10) for 37 hours per week. But 32 hours is possible too!
• Room to work hybrid and arrange your hours flexibly. Do you work two days or more per week from home? Then you will receive an allowance of € 45, - net per month.
• Engineering Laptop (Mac or Windows) and telephone.
• 8% vacation pay and 25 vacation days if you work full-time.
• Reimbursement of commuting expenses.
• A good pension plan through the PostNL pension fund.
• Training and development opportunities through the PostNL Academy.
• Discounts on vacations, events, and products.

This is what you bring

You are highly analytical, solution-oriented, and excel at collaborating within a multidisciplinary team. These qualities are crucial for translating complex challenges in AWS Serverless technology into practical solutions while working closely with colleagues and stakeholders. You also have a keen eye for detail and work meticulously, which is essential for maintaining our high standards in security, privacy, and customer focus.

Furthermore, you recognize yourself in the following:

• You have a higher education or university degree in a relevant field, such as Computer Science or Informatics.
• You have at least three years of experience in backend development within AWS Serverless technology, including CDK and, preferably, SageMaker.
• You are proficient in developing code in Python and TypeScript.
• You have experience with DevSecOps and Scrum, including automating build, test, and deployment processes.
• Basic knowledge of machine learning and an affinity for data analysis processes are a plus.