
Senior Machine Learning Engineer
- Stockholm
- Permanent
- Heltid
- Design, develop, and deploy scalable machine learning models for recommendation, prediction, and classification tasks
- Perform advanced statistical analyses to uncover trends in user behavior, content performance, and platform usage
- Translate business challenges into structured machine learning problems and deliver measurable solutions
- Collaborate cross-functionally with product, engineering, content, commercial, and marketing teams to drive strategic, data-informed decisions
- Build robust, production-ready pipelines and monitor ML systems in a cloud-native environment
- Contribute to a culture of experimentation, innovation, and continuous learning within the data team
- Take ownership and lead end-to-end machine learning projects, from ideation and stakeholder alignment to development, deployment, and post-launch evaluation
- Lead Data scientist/Machine learning engineer forum
- Proven experience leading machine learning projects end-to-end, from problem definition and stakeholder alignment to deployment and performance monitoring in production
- 7+ years of hands-on experience in applied Machine Learning or Data Science within production environments
- Deep understanding of statistical modeling, machine learning algorithms, and their real-world applications
- Advanced programming skills in Python, along with solid experience in SQL and Apache Spark
- Solid experience deploying ML models in cloud environments (preferably AWS) using containerization tools like Docker
- Familiarity with orchestration tools such as Airflow, enabling reliable ML pipeline execution and monitoring
- Strong communication skills, with the ability to clearly explain complex technical concepts to both technical and non-technical stakeholders
- Demonstrated ability to build ML systems that are scalable, robust, and explainable, not just performant in isolation.
- Comfortable working in cross-functional, agile teams where priorities shift quickly and collaboration is key
- Strong academic background in Statistics, Mathematics, Computer Science, or another quantitative field
- Experience working on recommender systems, personalization, or content optimization — ideally in media, streaming, or e-commerce domains
- Familiarity with MLOps practices, including CI/CD for ML, model monitoring, and observability in production
- Knowledge of experimentation platforms (e.g., A/B testing infrastructure) and causal inference techniques
- Exposure to real-time or near-real-time ML architectures and streaming data systems
- We’ve got you covered! 30 days of paid vacation every year, an attractive pension and insurance scheme, and generous parental leave pay lift.
- Your wellbeing matters. We provide you with various wellbeing initiatives including wellness allowance.
- A safe space to grow and up-skill. Our learning culture puts you in the driver’s seat of your own development.
- An innovative environment with Hack Days once a year. This week-long initiative allows you to think outside the box and deliver creative, technical solutions that (more often than not) go on to be implemented, either in our product or our ways of working.
- Entertainment is what we love, and entertainment is what we do. So, unlimited access to Viaplay seems only fair for you to get to know the product – including serier & viewing events, new release movie rentals, linear channels and more.