ML Engineer

🚀 Are you our new ML Engineer?

Subscription Data Enablement is a team in Schibsted Media, part of the Subscription - Growth business unit. We’re on a mission to build modern, reliable and scalable data and AI capabilities that enable commercial growth through personalization, automation, and insight.

Our team consists of Analysts, Data Scientists, and Engineers who work across brands to develop AI/ML-powered solutions and data products that drive subscriber engagement and retention. As an ML Engineer, you’ll play a key role in bringing our AI models into production, bridging the gap between data science and engineering, and contributing to our growing ML infrastructure.

👩‍💻 Your responsibilities:

• Design, develop, and maintain scalable ML systems and infrastructure — from model training and deployment to monitoring and automation.
• Collaborate with data scientists and engineers to productionize models and integrate them into digital products and commercial workflows.
• Build and evolve robust data pipelines, APIs, and containerized environments that support reliable model serving.
• Support and improve our MLOps stack for testing, monitoring, reproducibility, and version control.
• Contribute to shared engineering tasks, tooling, and platform development when priorities align.
• Stay updated on ML engineering trends and help bring new practices and technologies into our stack.
  
  

🤝 Who are we looking for?

You enjoy building elegant, scalable systems and solving complex technical challenges with real business impact. You’re a hands-on engineer with a passion for operationalizing AI and supporting the teams who build models. You care about data quality, system performance, and getting things into production — and keeping them there.

The role is a great fit if you:

• Are fluent in Python, and experienced with ML/AI libraries like Scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Know your way around SQL and data warehouses (e.g. Snowflake).
• Have experience with cloud platforms (e.g. AWS), Docker, and preferably orchestration tools like Airflow or Dagster.
• Understand MLOps principles and have worked with tools for model versioning, monitoring, and deployment.
• Are comfortable designing and implementing end-to-end ML pipelines — from data ingestion and feature engineering to deployment and monitoring.
• Have strong collaboration skills and enjoy working closely with data scientists, engineers, and product stakeholders.
• Bonus: Have 2+ years of experience in ML engineering, MLOps, or related data/AI engineering roles.
• Bonus: Experience with real-time model inference, streaming data pipelines, or personalisation use cases.
  
  

🌱 What’s in it for you?

• A hybrid, informal, and collaborative work environment across Norway and Sweden.
• The chance to work on impactful ML solutions used by millions of users across leading Nordic media brands.
• A place in one of the largest data communities in the Nordics, with great opportunities for personal and professional development.
• Strong cross-functional collaboration with commercial, product, and editorial teams.
• Competitive salary and benefits, and exciting career opportunities within Schibsted Group.
  
  

🏢 Work location:

Oslo or Stockholm (Hybrid)

📰 About Schibsted Media & Subscription

Schibsted Media is home to some of the Nordics’ strongest news brands – including VG, Aftonbladet, Aftenposten, E24, Svenska Dagbladet, and Omni – with over 700 million monthly visits. The newly established Subscription business unit owns the subscription experience end-to-end — from product and growth to personalization, data, and infrastructure.

We operate across Norway, Sweden, and Finland, working closely with Product, Tech, and Editorial teams to build the future of digital subscriptions and independent journalism.