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ML Engineer

Posted 1 week ago by Marita Ellberg
Stockholm
Application deadline closed.
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Job Description

Senior Machine Learning (ML) Engineer to join the AI/ML development team, tasked with building advanced AI-driven solutions within client’s comprehensive fashion network.

 

 

  • Develop and maintain AI/ML solutions, including exploring large datasets, feature engineering, building data pipelines, testing and evaluating model outputs, and deploying solutions for production use in a scalable manner.
  • Design and develop the large-scale data infrastructure needed for AI/ML projects.
  • Contribute to architectural decisions and technical roadmaps while ensuring code quality, maintainability, and scalability.
  • Develop reusable components and frameworks that address common needs in AI/ML, such as model traceability, monitoring, versioning, and online/batch inference serving.
  • Collaborate with cross-functional teams including engineers, data scientists, and business stakeholders to build and enhance the AI ecosystem.
  • You`ll have a key role in designing, developing, and maintaining AI/ML software products, contributing to innovative projects from conception to deployment at scale.

 

 

SKILLS:

 

  • 5+ years of professional experience in relevant roles for a Senior Machine Learning Engineer, with a strong focus on AI/ML development.
  • Strong software engineering background with hands-on experience in coding, DevOps, testing, and Site Reliability Engineering (SRE) principles, applied to AI/ML projects.
  • Proven experience developing and deploying software solutions to production in large-scale environments, ensuring product quality, cybersecurity, and performance.
  • Proficiency in modern programming languages, particularly Python (4+ years), with experience in back-end development and familiarity with FastAPI.
  • Expertise in cloud technologies, especially Google Cloud Platform (GCP) ML certification and Vertex AI, for cloud-based ML development.
  • Solid experience with MLOps practices, including developing ML pipelines and deploying applications to production.
  • A strong data science background with proficiency in various AI/ML techniques and frameworks.
  • Experience with high-volume heterogeneous data (both batch and stream), with expertise in SQL, DBT, and cloud data storage technologies.
  • Experience with requirement analysis, solution design, breaking down work into tasks, and collaborating with stakeholders to ensure implementation of organizational standards and best practices.
  • Familiarity with agile working methodologies and a strong focus on data-driven development.