Cloud Native AI/ML Solutions Architect

2 days ago


Stockholm, Stockholm, Sweden TN Sweden Full time

As a Machine Learning Engineer at TN Sweden, you will be part of a dynamic team that pushes the boundaries of innovation.

About Us
  • We are a leading recruitment agency in Sweden, dedicated to helping businesses find top talent.
  • We provide innovative recruitment solutions, streamlining processes, and minimizing costs.
Job Responsibilities

The Machine Learning Engineer will be responsible for:

  1. Developing and deploying AI/ML software products, including data exploration, algorithm development, feature engineering, model evaluation, and scaling for production usage.
  2. Designing and maintaining large-scale data infrastructure for AI/ML projects, ensuring scalability, maintainability, and future-proof architecture.
  3. Leveraging software architecture and design patterns to write efficient, well-designed, and future-proof code.
  4. Developing solutions, components, services, and frameworks to address common needs in AI/ML projects, such as feature reuse, model traceability, and A/B testing.
  5. Collaborating with cross-functional agile teams to build the AI ecosystem within the company.
Requirements
  • Bachelor's or Master's degree in computer science, engineering, or related field, or equivalent practical experience.
  • 4+ years of professional experience working in relevant roles for Machine Learning Engineers.
  • Hands-on coding skills with a strong background in software engineering practices for machine learning projects.
  • Experience developing software products successfully deployed to production.
  • Several years of coding experience in modern programming languages, with a strong background in Python programming (i.e., 3+ years).
  • Great experience with cloud technologies for ML development, preferably Google Cloud.
  • Solid experience in MLOps practices, developing ML pipelines, and deploying ML applications to production.
  • Strong working knowledge of various AI/ML techniques and experience working with different frameworks.
  • Experience handling high volume heterogeneous data (both batch and stream) and a solid understanding of data structures, databases, and data storage technologies.
  • Familiarity with agile ways of working, team collaboration, data-driven development, and reliable experimentation.


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