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We are currently looking for a talented Senior Backend Engineer to join our Machine Learning Team in Stockholm. The vision of our team is to be the best at understanding content and embedding this knowledge in all of Schibsted products in order to increase their business value. We collaborate closely with product and engineering teams to build models and services that add value in terms of, e.g., increased relevance, automation, and personalization.
Here are some examples of ongoing or planned machine learning work in Schibsted:
- Personalization and moderation of media content
- Image processing and classification
- Content recommendation & classification using Natural Language Processing (NLP)
In this role you will:
- Contribute to designing, building, training, evaluating, shipping, and refining ML-driven products
- Collaborate closely with a cross-functional agile team spanning data science, product management, and engineering to build prototypes as well as production-ready solutions
- Consider engineering as a whole by making the pragmatic tradeoffs in terms of security, performance, maintainability, availability, and cost
- Coordinate work across team boundaries
- Foster a culture of mentorship and knowledge sharing within the team
Who you are:
- You are experienced in Python programming, probably also other languages
- You have experience taking things from idea to code to production
- You can drive and take responsibility for quality and delivery
- You are comfortable with basic ML concepts
- You have experience working with cloud platforms, preferably AWS
- You have strong communication skills and you are comfortable in discussions
- You have 4+ years of experience from engineering roles
Schibsted Data & Tech is a central product and tech unit that serves all of Schibsted. We are about 250+ people in Oslo, Stockholm and Krakow, and collaborate closely with other product and tech teams in all units in Schibsted. Areas of responsibilities include data & technology strategy, privacy/data trends/responsible data & machine learning, information security and internal IT.