Related skills
azure aws sql python google cloud📋 Description
- Translating requirements: interpret vague needs to build models.
- Data science: run ML experiments with libraries.
- GenAI: leverage generative AI for innovative solutions.
- Optimisation: optimise ML for performance and scalability.
- Data engineering: ensure efficient data flow between databases and backends.
- MLOps: automate ML workflows, testing, reproducibility.
🎯 Requirements
- Experience: Multiple years as ML Engineer, preferably with consulting background.
- Programming: Python backend in production-ready CI/CD pipelines.
- Cloud: Google Cloud, AWS, Azure expertise.
- SQL: Strong querying and data management.
- ML integration: Exposing ML components via web services (e.g., Flask).
- Soft skills: Strong communication and presentation abilities.
🎁 Benefits
- Holiday: 30 days plus bank holidays
- Health: 4500 kr/year healthcare allowance
- Wellbeing: Up to 5000 kr/year wellness allowance
- Hybrid: 1200 kr WFH equipment allowance
- Learning & Growth: Udemy access
- Pension: Private salary sacrifice pension
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