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
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