Senior MLOps Engineer

PLP Group; Stockholms kommun; On-site; SEK 775,398 - 868,446; Full time

Job summary

Klarna in Stockholm is seeking a Senior MLOps Engineer to bridge engineering and data science, turning models into reliable production systems for credit decisioning.

You will write Python to train models, build scalable ML pipelines, and deploy them into production using AWS SageMaker and other cloud tools, ensuring reliability and observability across the stack. Fluency in English is required.

Qualifications

• Strong experience with Python for data science and ML development.
• Hands-on productionizing ML models and pipelines.
• Experience with tree-based models.
• Experience with AWS or comparable cloud infrastructure.
• Understanding of MLOps practices for scaling models to production.
• Experience collaborating with cross-functional teams.
• Working proficiency in English (written and spoken).

Responsibilities

• Build and productionize ML pipelines powering Klarna's credit decisioning.
• Write Python to train models and build data processing workflows.
• Deploy models into production using cloud infrastructure and tools.
• Collaborate with data scientists and engineers to scale data science capabilities.
• Monitor models and support observability in production.

Skills

Python for data science

ML pipeline productionizing

Tree-based models

AWS / cloud infrastructure

MLOps practices

Cross-functional collaboration

English communication

Tools

AWS SageMaker

Job description

Senior MLOps EngineerJob detailsEngineeringStockholmFull-timekr 775,398 SEK - kr 868,446 SEKAs a Senior Engineer, you will work at the intersection of engineering and data science, building and productionizing machine learning pipelines that power Klarna's credit decisioning. You will take models from development through to production, ensuring pipelines are reliable, scalable, and ready for real-world use. Your day-to-day work will span writing Python to train models, building infrastructure to support the ML pipeline, and deploying models into production using tools such as tree-based models, AWS SageMaker. You will play a key part in scaling Klarna's in-house data science capabilities as we continue to grow our credit risk and fraud offerings. Who you are* Strong experience with Python for data science and machine learning development* Hands-on experience productionizing machine learning models and pipelines* Practical experience with tree-based models* Experience with AWS or comparable cloud infrastructure* Understanding of MLOps practices for scaling models into production* Experience collaborating with cross-functional teams* Working proficiency and communication skills in verbal and written EnglishAwesome to have* Experience working in credit risk, fraud, or financial services* Experience building data pipelines at scale within a larger data science organization* Familiarity with model monitoring and observability tools* Experience with CI/CD tools for ML deploymentPlease include a CV in English