Senior Machine Learning Engineer | Stockholm
Workplace: Stockholm, Sverige
Expires: November 13, 2025
Join Apotea, Sweden's leading online pharmacy, as a Senior Machine Learning Engineer. Work on cutting-edge AI and ML projects that impact millions, building end-to-end machine learning systems, applying MLOps best practices, and collaborating in a dynamic agile team. Influence healthcare accessibility through innovative AI solutions in a stable, sustainable company.
Main requirements:
  • Extensive experience deploying production-grade machine learning models
  • Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
  • Strong system design and engineering skills with emphasis on maintainability and testing
  • Knowledge of cloud infrastructure, preferably AWS
  • Ability to mentor and guide junior engineers
  • Experience applying MLOps and DevOps practices including CI/CD and Infrastructure as Code
  • Strong collaboration skills to work across teams including Data Engineers, Software Engineers, Product Owners
  • Capability to define meaningful metrics and evaluation procedures
Responsibilities:
  • Build, deploy, and maintain end-to-end ML systems ensuring scalability and reliability
  • Integrate ML models into products delivering measurable business value
  • Apply MLOps and DevOps best practices such as CI/CD pipelines and cloud native solutions
  • Collaborate closely with cross-functional teams to align on data, architecture, and goals
  • Define and monitor performance metrics and validation frameworks aligned with business requirements
  • Initiate and implement continuous improvements to enhance productivity and quality
  • Mentor junior engineers providing technical guidance and code reviews
Required hard skills:
  • Python programming
  • Machine learning frameworks: TensorFlow, PyTorch, Scikit-learn
  • Cloud infrastructure (AWS preferred)
  • MLOps including CI/CD pipelines and Infrastructure as Code
  • Production deployment and monitoring of ML models
  • Strong software engineering practices including testing and documentation
Recommended hard skills:
  • Feature stores
  • Real-time inference pipelines
  • Open data formats such as Delta Lake or Iceberg
  • Swedish language skills (not mandatory)
Soft skills:
  • Mentorship and leadership
  • Problem-solving and proactive risk management
  • Collaboration and communication
  • Innovation balanced with practical constraints
  • Ownership and accountability
Coding languages:
  • Python
Frameworks:
  • TensorFlow
  • PyTorch
  • Scikit-learn
Natural languages:
  • English (Expert)
  • Swedish (Basic familiarity)
Cultural skills:
  • Agile methodology
  • Sustainability focus
  • Diversity and inclusion awareness
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