Data Science Engineer - Search Department (SED) at Rakuten

Tokyo, , Japan -

Full Time

Start Date

Immediate

Expiry Date

03 Apr, 26

Salary

0.0

Posted On

03 Jan, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, NLP, Computer Vision, Python Programming, Data Analytics, Deep Learning, Multimodal Tasks, Neural Networks, Optimization Techniques, Semantic Search, Image Search, Deep Ranking Systems, AB Testing, Software Development, Communication, Teamwork, Problem Solving

Industry

Software Development

Description

Job Description: Business Overview The AI & Data Division (AIDD) creates powerful AI, customer-focused search, recommendation, data science, advertising, marketing, price and inventory optimization solutions to a variety of businesses in commerce, fintech and mobile industries. We design, develop, and deploy high performance, fault-tolerant distributed systems used by millions of Rakuten customers every day. We strive to deliver the most innovative solutions that are helpful to people and societies around the world. Rakuten is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At Rakuten, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too. Department Overview 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. Position: Why We Hire 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. Position Details 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. Responsibilities - 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. Mandatory Qualifications: - 2 year or more experience in one or more of the following areas: Machine Learning, Search, Recommendation Systems, Large Language Models, or other related areas. - Bachelor's in computer science or a related technical discipline, Master or PhD preferred. - Solid experience with data structures or algorithms. - Strong software development experience through hands-on coding in a general-purpose programming language. - Strong communication and teamwork skills. - Passion for technology and solving challenging problems. #engineer #datascientist #aianddatadiv In Japanese, Rakuten stands for ‘optimism.’ It means we believe in the future. It’s an understanding that, with the right mind-set, we can make the future better by what we do today. So we challenge ourselves to evolve, innovate and experiment, to create a better, brighter future for everyone. Today, our 70+ businesses span e-commerce, digital content, communications and fintech, bringing the joy of discovery to almost 1.3 billion members across the world. If you have any trouble logging in, please contact us here Rakuten Group, Inc.: rakuten-recruiting-info@mail.rakuten.com *Please read the Application Requirements(EN) / 募集要項(JP) before applying. Our Diversity & Inclusion Policy and Application Documents Rakuten’s corporate mission is to “contribute to society by creating value through innovation and entrepreneurship.” We foster a culture that provides equal opportunities to those who share this founding philosophy and take on the challenge to transform society, regardless of age, gender, nationality, or any other status. Diversity is one of Rakuten's core strategies and a driving force for innovation. Because of this, you are not required to submit any of the following information in order to apply for our job positions. - Gender - Age - Photo - Nationality* - Information not related to business, such as ideological beliefs, family structure, etc. * For legal compliance, we may ask you about your work eligibility. See the details

Responsibilities

The search science team develops advanced deep learning models and algorithms for various NLP and multimodal tasks. They focus on improving search recall and ranking, conducting AB tests, and ensuring successful deployment of features and models in production.