🚀 MLOps / Machine Learning Engineer

✅ Build scalable, production-ready ML systems

✅ Bring models from experimentation to real-world impact

✅ Work at the intersection of Data Science, Engineering & Cloud

💡 The role

As a Machine Learning Engineer, you play a key role in bringing machine learning solutions into production. You will work closely with data scientists and engineers to ensure models are scalable, reliable, and deliver real business impact.

You will spend:

4 days per week working as an ML Engineer at one of our partner organizations
Every Friday at our office in Amsterdam, where you receive ongoing technical training and support from our leads
At the end of your first year, you will have the opportunity to transition into a permanent role with the partner organization.

🔧 In this role, you would:

Build and maintain end-to-end ML pipelines
Deploy and monitor models in production (including versioning and retraining)
Work with tools such as Databricks, MLflow, and CI/CD pipelines
Contribute to the MLOps lifecycle and help improve standards and best practices
Collaborate closely with both technical teams and business stakeholders

⚙️ Tech stack

Python & Spark
Azure (ADLS, Databricks) & AWS
MLflow / MLOps tooling
Docker / Kubernetes
Airflow

🧠 Your profile

You are a hands-on engineer who enjoys working on the full machine learning lifecycle. You like building systems that are not only technically strong, but also usable and scalable in real-world environments.

You bring:

A technical Bachelor’s or Master’s degree (e.g. Data Science, AI, Econometrics)
3–4 years of experience as a Machine Learning Engineer or Data Scientist
Experience with deploying, monitoring, and maintaining ML models in production
Strong programming skills (Python) and experience with distributed data processing (e.g. Spark)
Familiarity with MLOps concepts, CI/CD, and cloud environments
Experience with tools such as Kubernetes, Airflow, Kafka or similar is a plus
Strong communication skills and the ability to work with both technical and non-technical stakeholders

🚀 What you’ll work on

You will be involved in a wide range of data & ML-driven projects, such as:

Building predictive models and deploying them into production
Developing scalable data and ML pipelines
Working on cloud-based architectures
Solving real-world challenges like forecasting, optimization, or fraud detection

🎓 About Xccelerated

Xccelerated is part of the Xebia Group and focuses on accelerating careers in Data, Cloud & AI. Our 13-month program combines hands-on project work with intensive training and coaching.

You’ll join an ambitious data & AI professionals team.

🎁 What we offer

💰 Competitive salary
🛫 25 vacation days
📊 Weekly training & innovation days (1 year)
💻 MacBook & iPhone
🍎 Lunch, coffee & snacks at the office
🎒 Flexible working (home & office)
🚀 Fast-track career growth into senior roles

📩 Interested?

We’d love to get in touch!

Contact Samantha Alves Goncalves

📧 sgoncalves@xccelerated.io

📞 +31 6 13 88 97 70

⚡ Application process

Introductory interview with our recruitment team
Technical assessment (from home) + discussion with our Tech Leads

👉 We aim to complete the full process within 1–3 weeks (depending on your availability)

Xccelerated | Part of Xebia

Vacatures

Machine Learning Engineer