Machine Learning Engineer (Recommendation)/Generative AI

【About the company ...】

The company is a Web3 startup that aims to create a fan economy with the mission of "advancing the times together with fans".
The company develops and provides a fan platform for the Web3 era that maximizes fan enthusiasm for major entertainment companies such as publishers, music labels, and game companies. They have raised 3.4 billion yen in Series B funding in 2022 and are actively recruiting.

The company uses the concept of a "Decentralized Autonomous Organization (DAO)" as a guideline for organizational management.
Regardless of age, role, or position, members proactively make proposals and decisions.

The company aims to realize new entertainment experiences at the production level by utilizing generative AI technologies, such as Generative Agents and Entertainment IP's unique image generation.

Agile: To respond flexibly to areas of high uncertainty, we use Kanban to manage development autonomously by teams of engineers.

【 Job Description 】

The company is a Web3 startup with the mission of "advancing the times together with fans".
The company aims to realize a "Fan Nation," an economic zone where fans co-create with their "likes" and "passions" beyond national borders by utilizing cutting-edge technologies such as blockchain and generative AI.

The company is currently developing and providing a fan community platform for major entertainment companies and operating a service for researching and developing new finance. They continue to take on global challenges by leveraging the strengths of Japan.

To further advance the platform service, the company is currently implementing and operating a content recommendation engine.
They are looking for a machine learning engineer who will work with us to create the best fan experience possible.


- Research and implementation of algorithms to recommend content in the app according to user preferences
- Effectiveness measurement, parameter update, and tuning of existing recommendation engines
- Research and study of new recommendation algorithms

*Python is assumed to be used on Colab.


・Weekly Shonen Jump "The Promised Neverland" Official Community


・Development language: Golang
・Cloud: AWS / GCP
・Container technology: Docker
・Monitoring: Stackdriver / CloudWatch
・DB: Cloud Datastore / MySQL
・Configuration management: CloudFormation
・CI/CD: CircleCI / GitHub Actions


・In-house study sessions (held weekly)
・All expenses for the purchase of books (including manga) are covered.
・Partial coverage of expenses for participation in study groups and events
・Covers the cost of paid service experience (for 3 months)
・Subsidy for the purchase of Ethereum (to promote the use of blockchain services)
・Other services such as gym, laundry and housekeeping (up to 20,000 yen/month in total)

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【 Working time 】

Flextime System

【Holidays】
・Saturday/Sunday/National Holiday
・Annual Paid Leave
・New Year Holida
・Nursing Care Leave
・Congratulations & Condolence Leave

【Welfare】
・Fully remote working in principle (with one day of work per month)
・2 days off per week, holidays off
・Annual paid vacation (10 days granted on the day of employment)
・Year-end and New Year vacations
・Condolence leave, nursing care leave

・Rent subsidy (for those within 3 km of the office or within 3 stations from Sasazuka or Daitabashi station): 10,000 yen if rent and common expenses are less than 70,000 yen, 20,000 yen if rent and common expenses are 70,000 yen or more
・Full subsidy for the purchase of books (including manga)
・Subsidy for participation in outside study groups and events
・Up to 20,000 yen per month for laundry, housekeeping, gym fees, etc., selected by each employee from among items specified by the company.
・Subsidy for Ethereum purchase
・Subsidy for remote work environment...up to 100,000 yen

Required
- Experience in practical applications of machine learning model implementation and mathematical optimization (e.g., you have experience in the following)
- Experience in researching and writing papers on mathematical and statistical models at a university/research institute.
- Experience in building models in an AI startup or R&D team of a mega-venture.
- Experience as a quant/actuary at a financial institution.
- Experience in utilizing statistical packages such as pandas, sklearn, pytourch, tensorflow, etc. to efficiently perform and have performed appropriate preprocessing while understanding the basic statistics of noisy data.
- Knowledge of basic statistics such as classical statistics, Bayesian statistics, time series analysis, etc.

Preferred
- Able to read and implement the latest academic research and white papers

Ideal Applicants
・Able to think of strategies and tactics to achieve goals, communicate them to the team, and lead with a high level of motivation.
・Able to proactively tackle all issues within the company with a high sense of responsibility, without fixing the scope of his/her duties.
・Able to take on the challenges of new technologies and areas in which they have no experience
・Enjoys constantly changing conditions and uncertainty, and is able to respond flexibly and with a sense of speed
・Enjoy the growth and success of the users of the community and the members you work with