Rakuten | Machine Learning Engineer


Machine Learning Engineer, Search & Recommendation - Machine Learning & Deep Learning Engineering Department (MDE)

    Machine Learning Engineer|Rakuten
    Machine Learning Engineer|Rakuten
    Machine Learning Engineer|Rakuten

Job Summary


Japan, Tokyo
Partial remote
Apply from Anywhere

Language requirements

English: Business
Japanese: Not required

Key skills

  • NLP

Job Description

Job role

Machine Learning Engineer

Job description

The Machine learning and Deep learning Engineering Department (MDE) is a group of engineers and scientists who specialize in natural language processing (NLP), search, and recommendation systems. We conduct state-of-the-art research and apply cutting-edge technologies, such as transformer model, dense retrieval, distributed GPU training, and large-scale machine learning, to a variety of Rakuten products and services. We are looking for passionate experts in machine learning research and engineering to join us in our journey to define the next-generation e-commerce experience.

The search and deep learning Models and Algorithms team is responsible for developing cutting-edge solutions for various NLP tasks using neural networks, machine learning algorithms, and optimization techniques. The team works on challenging problems such as semantic search, large language model (LLM) training, and more. The team also leverages state-of-the-art frameworks such as transformers to train and deploy efficient and accurate models. The ideal candidate for this team should have a strong background in deep learning, NLP, CV, Python programming, and data analysis.

Our Rakuten 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.
1. Build industry-leading search & recommendation system; develop highly scalable classifiers and tools leveraging machine learning; work on cutting-edge research models in NLP.
2. Understand product objectives and machine learning techniques; improve model and recommendation strategy.
3. Understand user behavior and apply ML algorithms to optimize E-commerce conversion and production experience.
4. Understand the diversity of Rakuten's business requirements, data, and assets; build cross-scenario technology backbones.
5. Work with Rakuten cross-functional teams to grow Rakuten in important regional markets.

Required skills and experiences

Basic qualifications

1. 1 year or more experience in one or more of the following areas: machine learning, search, recommendation systems, data mining, or other related areas.
2. Bachelor or higher degree in computer science or a related technical discipline.
3. Solid experience with data structures or algorithms.
4. Software development experience through hands-on coding in a general-purpose programming language.
5. Strong communication and teamwork skills.
6. Passion for technology and solving challenging problems.

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.

Job Details

Employment typeFull-time
LocationRakuten Crimson House, 1-14-1 Tamagawa, Setagaya-ku, Tokyo158-0094
(1 min walk from Futakotamagawa Station on the Denentoshi Line)
Apply fromAnywhere
Remote workPartial remote
Working hours9:00am - 5:30pm (Every Monday, work hours are from 8:00am to 4:30pm due to morning meeting)
Holidays・2 days off per week (Saturdays, Sundays, and national holidays are holidays)
・10-20 days of annual paid vacation (the minimum number of days is the number of days granted after six months of employment)
・120 days off per year
In addition, year-end and New Year vacations, paid vacation, congratulation or condolence leave, maternity and paternity leave, etc.
*Once a year, you can take 9 to 12 consecutive holidays by using the long vacation (Success Vacation) system.
Employee benefits・Commuting allowance
・Housing allowance
・Health insurance
・Employee pension insurance
・Unemployment insurance
・Workers' accident compensation insurance
・Retirement allowance system
Supplemental education and qualification support
・English learning support (in-house TOEIC(R) test IP test, English conversation, etc.)
・Career challenge system (challenge the department of your choice)
・Job return system (rehiring system for those who retired due to marriage, childbirth, nursing care, etc.), etc.
・Stock Option Plan
・Cafeteria system with three free meals
・LILO Club (preferential treatment at sports clubs, accommodations, leisure facilities, movie theaters, etc.)
・LILO Club (sports clubs, lodging, leisure facilities, movie theaters, etc.) (Running, mountain climbing, cooking, etc., part of the expenses paid by the company)
・Reward system
・Free English conversation lessons by native English speakers
・Support system for certification acquisition
・Qualification support system, etc.
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