ML Operations Engineer
Workplace: Stockholm, Sverige
Expires: August 15, 2025
Join Electrolux Group's AI team as an ML Operations Engineer to architect, implement, and maintain scalable, reliable AI systems using modern AIOps techniques. Collaborate with data scientists to deploy production-grade AI solutions, apply best software engineering practices, and contribute to advancing the company's Data & AI transformation.
Main requirements:
  • Bachelor's or Master's degree in Computer Science or equivalent
  • Minimum 2 years of experience as an MLOps or ML Platform Engineer
  • Strong coding skills in Python and PySpark with modern Python tooling
  • Experience with software engineering best practices including automated testing, code reviews, packaging, and design patterns
  • Experience with CI/CD pipelines for ML workloads
  • Familiarity with model tracking and lifecycle tools
  • Experience with DevOps and orchestration tools
  • Working knowledge of Microsoft Azure services including Azure Foundry, AKS, and Container services
  • Experience in monitoring and LLMOps technologies
  • Good understanding of cloud networking and security fundamentals
  • Understanding of distributed data processing frameworks
  • Solid grasp of Python concurrency techniques
Responsibilities:
  • Collaborate with Data Scientists and partners to deliver production-grade, scalable MVPs
  • Design AI/ML operations architectures for reliable and scalable AI systems
  • Apply software engineering best practices to ensure quality and maintainability
  • Provide MLOps support and assurance for AI solutions
  • Co-own ML/AIOps architecture backlog and contribute to roadmap and architecture decisions
  • Enable AI observability collaboratively across teams
  • Enhance frameworks for streamlined MLOps and production deployment
  • Develop and enhance AIOps frameworks for agentic systems
  • Contribute to continuous development and ways of working within the AI team
Required hard skills:
  • Python programming and PySpark
  • Modern Python tooling (Pydantic, UVicorn, ruff, FastAPI)
  • Automated testing (Pytest)
  • Code review practices
  • Packaging tools like Conda and Docker
  • CI/CD pipeline management (e.g. GitHub Actions)
  • Model tracking tools (MLflow, Kubeflow, Model Registry, Unity Catalog, Databricks)
  • DevOps and orchestration tools (Airflow, Databricks Workflows, Kubernetes, Helm, k9s)
  • Microsoft Azure services and deployment
  • Monitoring and logging tools (Azure Monitor, Grafana, API management)
  • LLMOps tools (Tracing, Evals, Embedding analytics)
  • Cloud networking and security (VNET, RBAC, Secrets management)
  • Distributed data processing frameworks (Spark, BigQuery, Apache Beam)
  • Python concurrency (threading, multiprocessing, asyncio)
Recommended hard skills:
  • Experience with agentic frameworks such as AutoGen or LangGraph
Soft skills:
  • Curious mindset
  • Strong collaboration skills
  • Ability to ideate and solve complex problems
  • Adaptability in a cross-functional and international team
Coding languages:
  • Python
  • PySpark
Frameworks:
  • FastAPI
  • Pytest
  • MLflow
  • Kubeflow
  • Conda
  • Docker
  • Airflow
  • Databricks Workflows
  • Kubernetes
  • Helm
  • AutoGen (preferred)
  • LangGraph (preferred)
Operating systems:
  • Microsoft Azure Cloud environment
Natural languages:
  • English (Proficient)
Cultural skills:
  • Appreciation for diversity and inclusion
  • Effective communication in a multicultural environment
  • Collaborative team-oriented mindset
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