Machine learning engineer for recommendation systems

You build models that go live, and you stay the owner once they run. Here you also build the platform underneath them, from scratch. For my client, a Dutch scale-up that is moving to AI-first, I am looking for an AI / ML engineer who sets the foundation and takes people along.

• Set up the ML platform from the ground up: infrastructure, pipelines, deployment and retraining
• Build models for matching, recommendations and predictions
• Decide how models and infrastructure are measured in production, with monitoring that shows drift before the business does
• Start from the data: filter large volumes of data, form a hypothesis and prepare the dataset
• Bring LLMs and AI APIs in where that is the fastest route to impact
• You work with data engineering, product and software engineering, and you talk directly to the business. Your manager leads the AI project, backs you and expects you to find your own path.

• At least 5 years as an ML/AI engineer, MLOps engineer or similar
• Bachelor or master in a technical field
• Strong in Python, with a high-code mindset
• Models you brought to production yourself and owned afterwards, ideally on a platform you set up from scratch
• DevOps experience: cloud, CI/CD and infrastructure as code
• You enjoy going to the business yourself and can explain a technical choice to a non-technical stakeholder

• Salary: up to 9,500 euro gross per month.
• You build the AI foundation instead of maintaining one. The organisation is at the start of this transition, so your choices decide what it looks like two years from now.
• Startup feel, with the security of a healthy company that has the budget to invest. Plenty of autonomy, short lines and a fun team.
• Travel allowance up to 300 euro per month, or an NS business card for your route
• Working from home allowance per day, at the maximum tax-free rate
• One-off home office budget of 500 euro net
• Pension scheme with no employee contribution
• 25 holiday days per year (fulltime) and 8% holiday pay
• Collective profit sharing, plus growth within the salary scale
• An internal training academy and external trainers, with real room to develop
• Laptop for business use