MLOps Engineer
Workplace: Stockholm, Sweden
Expires: June 30, 2025
We are looking for a skilled MLOps Engineer to join our team to scale our machine learning infrastructure. The role involves designing, deploying, and maintaining end-to-end ML pipelines for impactful data-driven products. The candidate will bridge data science and production, working with cross-functional teams to version, test, deploy, and monitor models supporting real-world multi-tenant applications. The engineer should be passionate about automation and building fast, secure, and robust systems, and part of an agile team valuing clean code, reproducibility, and observability.
Main requirements:
  • Hands-on experience building multi-tenant AI and machine learning systems.
  • Strong understanding of CI/CD pipelines and automation tools.
  • Experience with Kubernetes for scalable, containerized ML workloads.
  • Strong experience with cloud platforms, specifically AWS, and cloud-native tools.
  • Fluent in English and residing in Sweden.
Responsibilities:
  • Collaborate with team to make model training, development, and monitoring fast, scalable, and cost-efficient.
  • Work with infrastructure as code technologies to deploy and manage robust MLOps solutions.
  • Proactively suggest and implement improvements to ways of working within and beyond the team.
  • Stay updated with latest trends and technologies in MLOps, AI, and cloud computing, driving continuous innovation.
Required hard skills:
  • Building multi-tenant AI and machine learning systems
  • CI/CD pipelines
  • Automation tools
  • Kubernetes orchestration
  • AWS cloud platform
  • Infrastructure as Code
Recommended hard skills:
  • Knowledge of latest trends and technologies in MLOps, AI, and cloud computing
Soft skills:
  • Passion for automation
  • Collaboration
  • Proactivity
  • Agility
  • Strong foundation in modern MLOps practices
Frameworks:
  • Kubernetes
Natural languages:
  • English (Proficient)
Cultural skills:
  • Working in Sweden
  • Collaborative and agile work environment