Natural Language Processing Researcher (LLM)

[About the Company]

The company's mission is "to advance humanity by reinventing the mechanisms of value creation" and aims to create an environment where people can focus on creating new value through the use of natural language processing and AI technologies.

AI delivers information directly related to business operations, thereby enhancing the information sensitivity of the organization. In addition, the company offers two SaaS products: "Anews," which encourages the conception of business ideas and their development within the organization, and "Astrategy," a market research service that provides suggestions by structuring necessary information according to the organization and its operations.

Currently, its main target is major manufacturing R&D in Japan, and more than 30% of the Nikkei 225 companies have already adopted the system. In the future, starting with manufacturing R&D, the company plans to expand to domestic enterprise companies, then to Japanese companies as a whole, and even to global companies.

The company completed a Series C financing of 1.1 billion in August 2022.
In February 2024, they were selected for the "GENIAC (Generative AI Accelerator Challenge) Project" promoted by the Ministry of Economy, Trade and Industry and NEDO, and have begun to develop their own LLM with 100 billion parameters!
The company has grown to 100 employees and is looking for more personnel to achieve further growth!

【Job Description】 

【Mission】
The Research Division conducts research and development on natural language processing and machine learning, and works closely with the product team to develop natural language processing and machine learning features for the product. They also conduct joint research on knowledge graphs with the Inui Laboratory at Tohoku University and publish "Introduction to Natural Language Processing with BERT (Ohmsha)".
In this position, you will be responsible for leading the research and development of natural language processing and machine learning in the Research Division.

【Responsibilities】
・Development of natural language processing and machine learning functions for products
・Development of methods for structuring news articles using eigenexpression extraction, text classification, etc.
・Construction of business-useful knowledge graphs from news articles
・Development of methods for recommendation of news articles
・Research and development of text summarization and text generation from news articles, papers/patents, and business documents in general

*Scope of change: Development-related work

【Development Environment】
[Organizational Structure]
Research Division (9 members) - LLM Unit (3 members)

[Main Languages]
Python

【Attractiveness of this position】
・Able to conduct research and development using data from the Anews news database of more than 100 million articles and user logs from 250 major companies
・Develop products using state-of-the-art machine learning and natural language processing technologies
・Top runner in the field of natural language analysis in the Japanese language and business domain
・Close proximity between R&D and product development, making it easy to incorporate R&D results into products

【Working conditions & treatment】

■Salary increase (twice a year / May and November)

【About remote work】
■Basically, fully remote work
　Residence must be in Japan (no full remote work while residing overseas)
■Flexible remote/working options (no restrictions on the number of times you can come to the office)
　Each employee works while using the system according to his/her own circumstances.

There are people who work full remotely from Sendai, Kyoto, Osaka, etc., people who enjoy working while on vacation, foreign nationals who return to their home countries for a few weeks to work, and people who mainly come to work, making for a diverse work style.

【Welfare】
■Customer facing allowance (flat monthly amount of 20,000 yen *included in monthly salary)
　Free use for self-improvement and customer value improvement
　(purchase of books/attendance at seminars/equipment, etc.)
■Lump-sum allowance for preparation for remote work (flat rate of 50,000 yen in the first paycheck)
　Provided as an expense for preparation for remote work

【Others】
■Periodic health checkups (all paid by company)
■Influenza vaccination
■PC of your choice provided
■Free drinks such as water/coffee/carbonated drinks/alcohol provided at the office
■Office Glico installed

【Education and Skill Development】
■Onboarding for 5 days after employment is available
■Monthly study day system (for own skill improvement and learning purpose)

【Internal Communication】
■Weekly company-wide online meeting
■Monthly social gathering (offline, some online)
■Semi-annual kick-off (hybrid of online and offline meetings)

【Holidays and Vacations】
■123 days off per year
■Saturdays, Sundays and national holidays (2 days off per week)
■Year-end and New Year vacations
■Paid leave (granted at the time of employment *Number of days granted depends on the month of employment)
■Prenatal leave
■Childcare leave

【Required】
*Meet all of the following
・Deep knowledge and work experience in natural language processing
・Completion of a graduate degree in science or engineering

【Preferred】
①Experience in research and practice in any of the following technologies
・BERT or other deep learning language models
　・Eigenexpression extraction, text classification, relation extraction
　・Knowledge graphs
　・Sentence generation, machine translation
　・Parsing, dependency parsing, semantic parsing

②Achievements in acceptance of papers at peer-reviewed international conferences and in English-language academic journals

【Ideal Applicants】
・Intrinsically interested in technology and willing to be a leading expert in the field
・Enjoys reading papers and following and testing the latest theories
・Able to communicate with the business side and think about how to deliver to customers and grow the business


・Able to live in Japan
・Able to communicate smoothly in Japanese, including technical details related to development.
　Reference: Daily conversation level.