★Machine Learning Engineer | Global Internet Business

• Business Level Japanese Required

✦Flextime & Fully Remote Work

✦Global Environment

✦Start-up Company

★Annual salary: 7 million yen - 12 million yen

【About the company】

【Unleashing the potential of the manufacturing industry】

The company will create a society in which all people involved in manufacturing can maximize their inherent power.

To achieve this goal, they will create a "new mechanism" that will change the common sense of industry.

Busy with estimating and administrative tasks, lacking sales skills, and lacking information and networks.

By untying these shackles, the potential of each company can be unleashed.

From small factories in town, to large manufacturers with a long history, to start-ups in their early years, all manufacturing companies will shine by leveraging their strengths to create new value.

They will continue to take on the challenge to open up such a future.

◆Flat organization

Regardless of your position, team, previous experience, gender, age, etc., you can express your opinions and immediately incorporate what is good.

◆Excellent members

The team is made up of members who have been active in leading companies. You will have an environment where there is a growth and stimulation every day.

◆Engineer Driven

Since they are operating in a field where there are no precedents yet in the world, technical skills are extremely important, and engineers play a leading role.

◎A service that uses automated quotation technology to connect custom-orderers with processing companies.

The manufacturing industry is Japan's key industry, boasting a gross domestic product of 180 trillion yen.

In fact, about 120 trillion yen of that is accounted for by the cost of parts procurement.

Despite this large percentage, there has been no major innovation in the procurement field for over 100 years.

In particular, parts procurement for the high-mix low-volume production industry, which accounts for about one-third of the total, has been facing various social issues on both the ordering and receiving sides, such as the time and effort required for ordering and quotation, procurement costs, and the high deficit ratio on the production side.

They believed that by solving these problems, manufacturers not only in Japan but also around the world would be able to focus on higher value-added work and maximize the potential of the manufacturing industry as a whole.

So, the company developed the world's first service that uses automated quotation technology to connect custom-orderers with processing companies.

【 Job Description】

【Responsibilities】

The Machine Learning Engineer is responsible for developing models in machine learning and data science, as well as building, maintaining, and operating the infrastructure that enables the continuous delivery of these models to the service. You will be expected to develop highly accurate modeling techniques that can leverage Caddy's data and provide value to our products, as well as develop stable systems in a team environment.

Examples of work are shown below. Actual duties are not limited to these. Your work after you join the company will be determined based on your skills, expertise, experience, and other factors.

・Construction of image recognition system for drawings

・Machine Learning Project Management

【Recruitment Background】

With the mission of "unlocking the potential of the manufacturing industry," the company is developing the "CADDi Drawer" data platform product for the manufacturing industry.

Launched in 2022, "CADDi Drawer" enables the utilization of drawing data, which is said to be the most important data in the manufacturing industry, as an information asset by structuring it through various technologies such as machine learning and linking it with various types of information. The system is already being used by customers ranging from major domestic manufacturers to processing companies, and is growing rapidly.

In the future, the company aims to realize overall optimization that transcends divisions and companies by using technology to reproduce and consolidate manufacturing industry knowledge in addition to drawings.

In terms of development, there are many themes we would like to tackle, such as enhancing the functionality of the data platform, developing multiple new applications that run on the platform, and strengthening the infrastructure to withstand the dramatically increasing number of users and volume of data.

The company is looking for people who can work together with us to develop products that are challenging and rewarding.

【About the Organization】

Engineers, designers, and product managers are divided into 10 or more teams of 4-6 members each, each working on various functional development (drawing utilization, search, estimation, etc.), data infrastructure development, machine learning/MLOps, R&D, enabling (QA/SRE), security, and other areas.

Aiming to achieve both "total optimization through standardization across teams" and "ensuring discretion and speed of each team," they have designed an organization that incorporates the concept of team topology.

20% of the development members are from overseas (Asia, Europe, North America, etc.). They are trying to create an organization in which multinational members can play an active role, for example, some teams communicate mainly in English, and important meetings are held in both Japanese and English.

【Development Environment】

Language

Front-end: TypeScript

Backend: Rust, TypeScript, Python

Frameworks and libraries

Frontend: React, , WebGL, WebAssembly

Backend: Rust (axum), (Express, Fastify, NestJS), PyTorch

Infrastructure: Google Cloud, Google Kubernetes Engine, Anthos Service Mesh

Database/Data Warehouse: CloudSQL (PostgreSQL), AlloyDB, Firestore, BigQuery

API: GraphQL, REST, gRPC

Monitoring: Datadog, Sentry, Cloud Monitoring

Environment construction: Terraform

CI/CD: Github Actions

Authentication: Auth0

Development Tools: GitHub, GitHub Copilot, Figma, Storybook

Communication tools: Slack, Discord, JIRA, Miro, Confluence

【 Requirements】

■Required

Basic knowledge of algorithms related to machine learning, statistics, linear algebra, and computer science

Experience working with machine learning to solve business problems

Experience improving the accuracy of machine learning and statistics models

Experience developing and operating APIs related to web services using Python, Rust, etc.

Experience working with cloud services such as Google Cloud and AWS

Basic knowledge of container technologies such as Docker

Experience in team development and operations using Git and CI/CD

Fluent business communication skills in Japanese

Ability to complete daily tasks in Japanese, including text communication and meetings

■Preferred

Experience in the following

Work related to image recognition, OCR and 3D analysis

ML project management or ML team lead

GPU-based data processing (CUDA, OpenCL, cudf, CuPy, etc.)

Machine learning pipeline development using Vertex AI Pipeline, kubeflow, Apache Beam, Spark, etc.

Continuously improve and deliver machine learning and data science models

Implement data quality measures to improve machine learning models in a Data-centric manner

Multiple winners in data analysis competitions such as Kaggle

Writing papers in leading journals in the fields of machine learning and data science

Application of numerical optimization methods to business problems

Developing front-end and back-end web services and distributed processing

■Ideal Applicants

Empathize with the company's mission and values

Willing to learn and challenge themselves with new technologies and things they have no experience with

Willing to catch up on relevant technologies required for ML/MLOps

Able to face essential issues and take actions to solve them with a sense of ownership

Able to work through positive attitude and constructive discussions in a fast-changing and uncertain environment

Able to communicate and discuss with others in a respectful manner, taking into account their context and resolution

【Working Time 】

Flextime System

【 Welfare 】

・Full social insurance

・Commuting allowance (up to 30,000 yen)

・Vacation (summer vacation, year-end and New Year's vacation, refreshment vacation, bereavement vacation, etc.)

・Subsidies (moving subsidies, child allowances, marriage congratulation money, etc.)

・Medical checkups

・Office medicine

・Office convenience store

・Learning support (book purchase system, language learning support, manufacturing experience, external training support, etc.)

・Company-wide awards

・Club activities

・Engineers can apply for a PC and display with their desired specifications.

※The maximum amount is 400,000 yen, within which you can also purchase accessories for the PC.

※The PC replacement cycle should be at least two years.

【 Holiday 】

• Saturday/Sunday/National Holiday
• Annual Paid Leave
• New Year Holiday
• Special Paid Leave
• Congratulations & Condolence Leave
• Bereavement Leave
• Refresh Leave
• Summer Holiday