As a Machine Learning Engineer, you’ll be a key part of our team, helping clients solve critical business challenges by designing, building, and maintaining intelligent systems. Your work will span across software engineering, data engineering, and applied machine learning. And turning complex problems into scalable, real-world solutions.
What You’ll Do
- Build end-to-end ML solutions: explore large datasets, experiment with models, engineer features, test and evaluate performance, and deploy to production.
- Develop components, services, and frameworks that support common ML needs. From feature reuse and version tracking to A/B testing and model monitoring.
- Work closely with cross-functional product teams to take ideas from concept to deployment, starting from business goals and ending with measurable outcomes.
- Own the reliability and scalability of production-grade models.
- Continuously improve team practices through collaboration, feedback, and knowledge sharing.
What We’re Looking For
We’re looking for someone with strong technical foundations, business focus, that likes to get things done!
- A degree in a quantitative field like computer science, mathematics, physics, bioinformatics, or similar.
- Fluency in Python and experience writing clean, production-level code.
- A sharp business sense.
- Experience working with cloud platforms and modern ML tooling.
- Comfortable with both batch and streaming data; you understand the tools and trade-offs for processing large-scale, heterogeneous datasets.
- Hands-on experience taking projects from business problem to deployed solution — and staying involved to measure and refine impact.
- Bonus if you have been deploying ML models in cloud-native environments
English 
Swedish