Artificial Intelligence Deployment Manager

4 days ago


Copenhagen, Copenhagen, Denmark Pandora AS Full time

Pandora A/S is seeking an Artificial Intelligence Deployment Manager to join its AI Team. The ideal candidate will be responsible for designing, developing, and maintaining end-to-end MLOps pipelines for model deployment, monitoring, maintenance, and scalability.

This expert will collaborate with cross-functional teams to ensure seamless integration of ML models into production systems. By automating model training and deployment processes, monitoring the performance of ML systems, and implementing improvements, this specialist will drive the operational efficiency of Pandora's AI and machine learning initiatives.

Responsibilities:

  • Design, develop, and maintain MLOps pipelines for model deployment, monitoring, and scalability.
  • Automate model training and deployment processes.
  • Collaborate with cross-functional teams to integrate ML models into production systems.
  • Monitor model performance and implement improvements.
  • Ensure scalability, reliability, and compliance of ML systems in production.

Requirements:

  • Education: Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field.
  • Experience:
    • Solid experience as a MLOps Engineer, Machine Learning Engineer, DevOps Engineer, or similar role.
    • Experience in the retail industry or e-commerce is highly desirable.
  • Technical Skills:
    • Strong experience with Infrastructure as Code frameworks and languages (Terraform, Bicep, or ARM).
    • Strong programming skills in Python and experience with ML frameworks (TensorFlow, PyTorch, etc.).
    • Hands-on experience with containerization (Docker) and orchestration tools (Kubernetes).
    • Proficiency in CI/CD tools and cloud platforms (AWS, Azure, or Google Cloud).
    • Knowledge of model monitoring and evaluation metrics.
    • Familiarity with version control systems, such as Git, and model versioning tools like MLflow or DVC.
  • Soft Skills:
    • Strong problem-solving skills with the ability to work independently and collaboratively in a fast-paced environment.
    • Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.


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