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Machine Learning Engineer Lediga konsultuppdrag · Stockholm
2 months ago
Job Summary
Deploja is seeking a highly skilled Machine Learning Engineer to join our team. As a Machine Learning Engineer at Deploja, you will be responsible for developing AI/ML software products, designing and maintaining large-scale data infrastructure, and working with cross-functional teams to build the AI ecosystem within the company.
Key Responsibilities
- Develop AI/ML software products including exploring large data sets, trying out new algorithms, feature engineering, testing and evaluating model output, deploying solutions for production usage, and scaling out for maintainable solutions in comprehensive fashion networks.
- Design and develop large-scale data infrastructure required for AI/ML projects.
- Leverage software architecture and design patterns to write scalable, maintainable, well-designed, and future-proof code.
- Develop solutions, components, services, and frameworks to address both specific and common needs in AI/ML projects, such as feature reuse, model traceability, monitoring, A/B testing, versioning, release, and serving of both online inference endpoints and batch inference.
- Work in cross-functional agile teams of highly skilled engineers, data scientists, and business stakeholders to build the AI ecosystem within the company.
Requirements
- Bachelor's or Master's degree in computer science, engineering, or a related field, or equivalent practical experience.
- 4+ years of professional experience working in relevant roles for a Machine Learning Engineer.
- Hands-on experience with software engineering and a strong background in Python programming.
- Experience with cloud technologies for ML development, preferably Google Cloud Platform, and including Vertex AI.
- Solid experience in MLOps practices, developing ML pipelines, data pipelines, and deploying ML applications to production.
- Strong working knowledge of AI/ML techniques and experience working with different frameworks.
- Experience handling and developing for high-volume heterogeneous data (both batch and stream), preferably including hands-on development in DBT, and a solid understanding of cloud data storage technologies and data quality.
- Experience from aligning and analyzing requirements, driving design solutions, breaking down work into stories and tasks, and making sure organizational standards and best practices are implemented and followed.
- Familiarity with agile ways of working, team collaboration, data-driven development, reliable and responsible experimentation.
