Data Science Engineer - Search Department (SED)

Search Department is part of the AI Engineering Supervisory Department under AI & Data Division in Rakuten. Search Department focuses on Search, Discovery, and Navigation experience for users of Rakuten. We help demand meet supply through our services that are engineered for scale, performance, and ease of use. We support 20 plus Rakuten Businesses across three different continents, 50 plus user functions and over a billion active users annually generating over two Billion dollars in revenue directly from us.

As an experienced Data Scientist, you will need to have a strong background in machine learning, NLP, Computer Vision, Python programming, and data analytics. Our team is responsible for developing state-of-the-art machine learning models and strategies to improve E-commerce conversion through search and recommendation algorithm improvements. You are able to work independently, and have the ability to propose solutions that the team can use, and that can impact projects.

The search science team is responsible for developing cutting-edge deep learning models and algorithms solutions for various NLP and multimodal tasks using neural networks, machine learning algorithms, and optimization techniques. The team works on challenging problems such as semantic search, image and multimodal search, deep ranking systems, and more. The team also leverages state-of-the-art frameworks such as transformers and large language model (LLM) to train and deploy efficient and accurate models.

Build industry-leading search & recommendation system to solve business challenges.

Develop highly scalable embedding-based retrieval systems and tools.

Be responsible for improving search recall and ranking by leveraging NLP and multimodal large models to improve multilingual, multi-task, and multi-modal algorithm performance.

Conduct AB Tests to ensure we pick the best winning variant.

Ensure successful deployment of features, code, data, and models in production.

Understand the diversity of Rakuten's business requirements, data, and assets; build cross-scenario technology backbones.

Work with Rakuten cross-functional engineers, researchers, and statisticians to grow Rakuten in important regional markets.