Rakuten Group

Rakuten, founded in 1997, is a Global Innovation Company based in Japan. With over 70 diverse businesses spanning e-commerce, digital content, fintech, and communications, and 32,000 employees, we serve 1.6 billion members worldwide. Our mission is to empower people and society through innovation and entrepreneurship.

Rakuten Tech in Europe

Rakuten Tech in Europe, a part of the Rakuten Group's Global Innovation Hub, serves as the regional hub for the European-based members of the Technology Division. We provide and optimize global platforms to support businesses within the Rakuten Ecosystem, tailoring them to specific use cases in Europe and beyond.

With over 130 members across 7 countries and 12 offices, our presence spans France (Paris), Spain (Barcelona), UK (Belfast and London), Estonia (Tallinn), and Germany (Berlin). Our diverse team is formed of more than 20 nationalities and collaborates with all members of the Technology Divisions on a regular basis.

Team’s presentation

Rakuten Institute of Technology (RIT) is the Research and Innovation Department of Rakuten, with teams spread across the globe. RIT is a unique environment for scientific research and innovations in the domain of Human-Computer Interactions, Computer Vision, Natural Language Processing, and Machine Learning.

As an intern, you will play a key role in exploring the potential of Multi-Objective optimization in the context of item recommendation and search. Your responsibilities will include the implementation of deep learning models for the recommendation/search task and evaluating the recommendation capabilities rankers under the multi-objective settings.

In more detail, you are expected to:

- Conduct a comprehensive literature review on learning-to-rank (LTR) with multiple objectives.

- Select the most relevant approaches for multi-objective LTR and implement them into our in-house Deep Learning repository.

- Investigate the effectiveness of multi-objective LTR on large-scale Rakuten data.

- Collaborate closely with the team to analyze and interpret experimental results.

- Extract meaningful insights that guide the design of new custom ranking models.

- Prepare and submit a scientific paper summarizing your research and findings.

Profile

- Currently enrolled in a computer Science Master 2 (or equivalent), specializing in Machine Learning or a related field.

- Strong proficiency in PyTorch for developing machine learning models.

- You are familiar with recommendation systems, deep learning with tabular data, natural language processing (NLProc), and machine learning techniques in general.

- Proven experience implementing ML papers.

- Experience with Git for version control and collaboration.

- Proven interest in recommender systems and information retrieval.

- Good mathematical background and problem-solving skills.

- Full proficiency in English and the ability to work independently and collaboratively as part of a team.

References

• https://arxiv.org/pdf/2306.05118.pdf
• https://arxiv.org/pdf/2107.08598.pdf
• https://arxiv.org/pdf/2105.02951.pdf

Benefits

• Compensation between 1100 and 1320 euros
• Restaurant vouchers
• Being part of multicultural teams with more than 20 nationalities
• Office in Sentier neighbourhood

As an employer, Rakuten Tech in Europe is committed to developing an inclusive working environment. Access to employment is open to all, regardless of gender, age, disability, ethnicity, religion, sexual orientation, or social status.