Basic Information

Client ID: 106000

Job ID: 2530

Position:

Location: Tokyo

Salary: 5M 8M JPY

Language: Japanese English (Business)

Contract type: Permanent

Who we are

AIAIAIAIAISDGsGRASP EARTH45

AI

AI

• English here

  We are a tech innovation firm that addresses business and societal challenges using solutions powered by AI and deep learning technologies. We specialize in MultiModal AI which combines various AI solutions to handle diverse data including image analysis deep learning anomaly detection AI using sensors and optimization AI. We are involved in every aspect of the process from strategic planning to requirement definition onsite consultation development and operational maintenance ensuring a comprehensive approach that delivers a return on investment. We have a track record of numerous achievements including automating waste incineration operations.

  Furthermore we actively engage with societal challenges and have received consecutive awards such as the 4th and 5th Space Development Utilization Awards for our work in discovering SDGs issues and environmental changes from satellite imagery including GRASP EARTH.

  In the future we will continue to pursue the heights of technology and business providing the highest level of solutions that allow society and our clients to experience sustainable results.

  Business Activities:

  • Consulting and development of AI and deep learning technologies.
  • Providing products through joint ventures licensing maintenance models and inhouse development.
  • Offering AI analysis solutions utilizing artificial satellite data.

Roles and Responsibility

• English here
  • Research devise and implement reinforcement learning areas to address client issues.
  • Participate in client meetings to report progress and discuss technical aspects of the project.
  • Work together with the architects to promote the project.

Minimum Requirements

• OSS
• English here
  • Basic knowledge of reinforcement learning and deep reinforcement learning in general
  • Ability and experience in implementing reinforcement learning methods using libraries and OSS.
    • The library used is not required but the ability to implement a method from scratch by oneself without using publicly available programs is a plus.
    • Ability to implement reinforcement learning methods from scratch by oneself without using publicly available programs is a plus.
  • Ability to research previous research using English
    • Ability to speak English at a conversational level including technical vocabulary is a plus.
  • Ability to explain difficult reinforcement learning methods in simple terms.

Preferred Requirements

Who you are

• 
  
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• English here

  • Experience in business system development

  Who you are

  • Those who share Ridgeis desire to pursue the best balance between business and cuttingedge technology.
  • Able to think and act independently and continuously to meet and exceed client expectations
  • Demonstrate leadership and teamwork in an environment of uncertainty and pressure.
  • Able to communicate proactively with members of the team who have engineering backgrounds.
  • Able to keep up with the latest technology trends including deep learning.

Conditions / Benefits

Employment type: Full time

Location: Chiyodaku Tokyo

Annual Salary: 5M 8M JPY (Negotiable)

Salary is determined based on experience and skills

Annual salary system (1/12 of the annual salary is paid monthly) Above includes 45 hours of overtime (additional overtime will be paid separately)

Salary review once a year (there are many cases of salary increases for high performance in just 6 months upon joining the company)

Bonus twice a year (January and July)

Hours: 9:30 18:30 (standard working hours: 8 hours)

General office hours: 9:30 18:30

Flexible working hours during probation

Core time: 10:30 16:30

Flexible time: (start) 7:30 10:30 (end) 16:30 20:30

Breaktime: 1 hour between 11:00 16:00

Two days off per week (Saturdays and Sundays)

National Holidays

Yearend and New Year holidays (December 28 January 4)

Refreshment leave (5 days after 1 year of employment)

Paid Holidays: 10 days of paid leave amount depends on the years of employment

Before annual paid leave is granted (6 months after joining the company) 3 days of special leave granted upon joining

Probation: 6 months

Benefits:

All transportation expenses are paid

Overtime allowance

Casual clothing is welcome

Telework consultation (frequency of attendance varies depending on the department and duties)

Insurance

• Employment insurance
• Workers accident compensation insurance
• Health insurance: Kanto IT Software Health Insurance Association membership
• Employee pension

Interview Process

1. CV Screening
2. Technical Test
3. 1st interview
4. 2nd Interview
5. Last Interview
6. Offer

Remote Work :

No