Machine Learning Engineer (Recommendation)

Job ID 20489
Job Type
Permanent
Salary
JPY 7,000,000 - JPY 10,000,000 per year
Japanese Level
None
English Level
High Intermediate (TOEIC 730)
Start Date
ASAP
Location
Tokyo
Job Type
Permanent
Salary
JPY 7,000,000 - JPY 10,000,000 per year
Japanese Level
None
English Level
High Intermediate (TOEIC 730)
Start Date
ASAP
Location
Tokyo

Description

A Japan-based startup focused on using new technologies to provide great Customer service in the spirit of "Omotenashi" is looking for a talented Machine Learening Engineer.

 

Responsibilities

- Research, design, and build ML systems for prediction, recommendation, and automation

- Select appropriate algorithms and fine-tune models for optimal performances 

- Evaluate model performance and suggest improvements where appropriate 

- Integrate machine learning models into production 

- Staying up-to-date with the latest machine learning technologies and methodologies 

- Execute critical phases within the ML lifecycle

【Company Details】

A new startup specializing in robotics based on the concept of OMOTENASHI, a company that wants to digitize the wonderful Japanese customer service and hospitality experience by providing chatbot technology and services to companies in various industries that are facing adversity due to COVID-19.

 

【Working Hours】

Flextime (Core Hours 1:00PM – 3:00PM) Hybrid system

 

【Holidays】

Saturdays, Sundays, national holidays, year-end and New Year holidays, paid vacations, other special vacations

 

【Services / Benefits】

WFH/remote work, long vacations (more than 2 weeks allowed), flextime, summer holiday, year-end holiday, childcare leave, congratulations/bereavement leave, company laptop provided, translation support, language learning courses, etc.

Required Skills

- Work experience as a Machine Learning Engineer or Data Scientist  in a leadership role
- Solid Machine Learning background and deep understanding of certain domain of machine learning techniques, especially in recommendation systems

- Familiarity with recommendation system algorithms, dimensionality reduction, and clustering

- Knowledge on AB testing, statistical sampling, and hypothesis testing

- Pytorch and Tensorflow skill