Machine Learning Engineer (EC AI)
Indexed description
Based in Singapore's Central Business District, Rakuten Asia Pte. Ltd. serves as the regional headquarters for Asia, driving value through areas such as advertising product development, product strategy, and data management to support Rakuten Group's global ecosystem. Learn more at: https://global.rakuten.com/corp/
The "AI Lab" organization within Rakuten is focused on advancing artificial intelligence applications across the company. It plays a key role in developing innovative AI solutions, and fostering collaboration to integrate AI into various Rakuten services.
Main Responsibilities
- Analyze assistant interactions and internal evaluations to identify improvement opportunities.
- Generate data-driven insights to guide product development and feature prioritization.
- Conduct research to improve agent architecture and user intent understanding to enhance response quality.
- Design and execute experiments, identifying the right metrics to evaluate impact.
- Collaborate with engineers and other Agent Science team members to implement and productionize improvements.
- Leverage diverse datasets across Rakuten’s ecosystem to improve assistant capabilities and deliver customer value.
- Clearly communicate findings and contribute to research and product decisions.
- Over 3 years of experience in data science, machine learning, or a related quantitative field.
- Strong Python and ML skills for data processing, analysis, and prototyping.
- Proficiency in SQL and working with large-scale structured data.
- Solid foundation in statistics, experimental design, and predictive modeling.
- Possesses strong problem identification and formulation skills, with a track record of proactively identifying potential issues and developing effective solutions.
- Demonstrated ability to thoroughly research and evaluate potential solutions and identify the optimal approach for a given problem.
- Excellent written and verbal communication skills, with the ability to clearly articulate complex technical concepts to both technical and non-technical audiences.
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