Senior Machine Learning Engineer – Stockholm (Onsite)
Workplace: Stockholm, Sweden
Expires: October 25, 2025
As a Machine Learning Engineer, you will contribute to developing and deploying AI/ML-based software products globally. Collaborate with engineers, data scientists, and stakeholders to design scalable solutions.
Main requirements:
  • 4+ years experience in machine learning engineering
  • BSc or MSc in Computer Science, Engineering, or equivalent practical experience
  • Strong coding skills with 3+ years in Python
  • Experience deploying ML models into production
  • Familiarity with modern programming languages and software development practices
  • Experience with cloud-based ML tools (preferably Google Cloud/Vertex AI)
  • Solid understanding of MLOps, pipelines, and deployment strategies
  • Experience with large-scale heterogeneous data (batch and streaming)
  • Comfortable working in agile teams
  • Cloud certification (GCP, Azure, or AWS) required or expected within one month of start
Responsibilities:
  • Develop AI/ML software products end-to-end: data exploration, feature engineering, model evaluation, deployment, scaling
  • Design and maintain large-scale data infrastructure for ML projects
  • Write clean, scalable, maintainable code following solid engineering principles
  • Build reusable components and services for ML workflows such as feature reuse, model traceability, A/B testing
  • Collaborate in cross-functional agile teams to enhance the internal AI ecosystem
Required hard skills:
  • Machine Learning Engineering
  • Python programming
  • ML model deployment
  • Cloud platforms (GCP/Vertex AI preferred)
  • MLOps and pipelines
  • Software development best practices
  • Data engineering for large-scale batch and streaming data
Recommended hard skills:
  • Experience with other programming languages
  • Cloud certifications (GCP, Azure, AWS)
Soft skills:
  • Hands-on and technically sharp
  • Passionate about software engineering applied to ML
  • Agile team collaboration
  • Data-driven development mindset
  • Responsible experimentation culture
Coding languages:
  • Python
Natural languages:
  • English (Proficient)
Cultural skills:
  • Agile methodologies
  • Cross-functional team collaboration
  • Data-driven decision making