- Interpret vague requirements and develop models to solve real-world problems.
- Conduct ML experiments using programming languages with machine learning libraries.
- Leverage generative AI to develop innovative solutions.
- Optimise machine learning solutions for performance and scalability.
- Implement tailored machine learning code to meet specific needs.
- Ensure efficient data flow between databases and backend systems.
- Automate ML workflows, focusing on testing, reproducibility, and feature/metadata storage.
- Create machine learning architectures using Google Cloud tools and services.
- Build and deploy production-grade software for machine learning and data-driven solutions.
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