【Unicorn Company/Fully Remote】Machine Learning Engineer【Intermediate Japanese Required】 Opportunity

royal agent company

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【Unicorn Company/Fully Remote】Machine Learning Engineer【Intermediate Japanese Required】 in GREATER TOKYO AREA

Visa sponsorship & Relocation 9 months ago

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▶︎Overview

*position : Machine Learning Engineer

*salary : from 8.5M JPY. to 12M JPY.

*language : English/Japanese(desirable)

*remote : Fully remote


▶︎About the Company

The company acts as a bridge between clients and processing companies such as local factories. The company is trusted by the ordering company for its consistent quality assurance of the machined parts delivered by the machining company, and the machining company can only receive requests that make the most of its strengths, providing a highly satisfactory service for both parties. The company has a clear vision of the issues it needs to tackle in the future, such as expanding the range of products and industries it handles, global expansion and the launch of new services, and in order to tackle these issues, it is aiming to build an organisation with 1,000 employees in three to five years and eventually become a trillion-dollar business, which is very promising. The company actively grants stock options and is a good environment for those who want to build value over the medium to long term.


▶︎About the Role

The Machine Learning Engineer will develop models in machine learning and data science, and build, maintain, and operate the infrastructure to continuously deliver these models to the service. The successful candidate 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.


Specific duties examples are:

・Construction of an image recognition system for drawings

Analyze drawing images and develop technology to extract information described on the drawings.

Extracting features from images, building, maintaining, and operating a similar image retrieval system using these features

Construction of image recognition models, and creation of annotation systems

Investigate the use of large-scale language models (LLM) and large-scale visual models (LVM)

Creating demos and reports of the created image recognition models and explaining the technology internally and externally

Experimentation, analysis, and visualization to ensure high model accuracy

Development and deployment of batch processing and API to extract information on drawings


・Construction of an analysis system for CAD data

Analyze CAD data and develop technology to extract necessary information from the information in CAD and 3D shape information.

Construction of CAD analysis models and algorithms, and creation of annotation systems.

Creating demonstrations and reports of the created CAD analysis models and explaining the technology internally and externally

Experiments, analysis, and visualization to ensure high model accuracy

Development and deployment of batch processing and API to extract information from CAD data


・Machine Learning Project Management

Project management of the development of machine learning models, including drawing analysis models.

Hearings from internal and external parties regarding issues related to drawing information and definition of tasks that can satisfy the requirements.

Discuss with the product manager and agree on KPI details and schedule for the machine learning models.

Define annotations as necessary, and collaborate with the annotation team as appropriate to create datasets.

Promote the examples of work described in Drawing Analysis and CAD Analysis, either by yourself or together with the machine learning engineers on your team


Examples of work are shown below. Actual duties are not limited to these. The duties to be performed after employment will be determined in consideration of skills and experience.



▶︎Development environment

  • Languages

-Front-end: TypeScript

-Backend: Rust, TypeScript, Python

  • Frameworks and libraries

-Frontend: React, Next.js, WebGL, WebAssembly

-Backend: Rust (axum), Node.js (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

(*Specifically relevant items are in bold.)


▶︎Salary

From 8.5M JPY. to 12M JPY.


▶︎Qualifications

【Required】

  • Basic knowledge of algorithms related to machine learning, statistics, linear algebra, and computer science
  • Experience working with machine learning to resolve business problems
  • Experience improving the quality 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

(ex: JLPT N2 level, 3 years of experience working in Japan,etc)


【Preferred】

  • Experience related to image recognition, OCR and 3D analysis
  • Experience in ML project management or ML team lead
  • Experience with GPU-based data processing (CUDA, OpenCL, cudf, CuPy, etc.)
  • Experience developing machine learning pipelines using Vertex AI Pipeline, kubeflow, Apache Beam, Spark, etc.
  • Experience continuously improving and delivering machine learning and data science models
  • Experience implementing data quality measures to improve machine learning models in a Data-centric manner
  • Experience winning multiple prizes in data analysis competitions such as Kaggle
  • Experience writing papers in leading journals in the fields of machine learning and data science
  • Experience in applying numerical optimization methods to business problems
  • Experience in web service development related to front-end and back-end
  • Experience in development and operation related to distributed processing


▶︎Work environment

Workplace

  • We primarily operate on a remote work basis
  • To encourage team interaction, we have recommended in-office days approximately once a week and off-site meetings 1 to 2 times a quarter
  • If you prefer to work from the office, you are welcome to use our office space at any time
  • Several team members also reside outside the Greater Tokyo area, including in the Chubu, Kansai, and Kyushu regions


Working Hours

  • Flextime (core time 11:00-16:00), including 1hour break, with overtime


▶︎Holidays and Leave

  • Annual paid leave (available after 6 months of employment) and special paid leave upon joining (3 days)
  • Summer vacation (3 days, available at your discretion between July and December)
  • Year-end and New Year's holidays (6 days)
  • Nursing and caregiving leave (up to 4 days per year) - Pets included
  • Refreshment leave (consecutive 5 days every 5 years of service)
  • Mourning and celebration leave


▶︎Allowances and Benefits

【Various Allowances】

・Transportation expenses paid (up to 30,000 yen per month)

>Residents living far from the office receive up to 60,000 yen per month

・Childcare allowance

>15,000 yen per month per dependent family member under 18


【Support for Employee Interaction】

・Club activity support fund (1,500 yen per member per activity)

・Teaming Offsite cost assistance (5,000 yen per person, up to once per quarter)

・Meal allowance for team internal interactions (2,000 yen per person, up to once a month)

・Meal allowance for interactions between different teams (3,000 yen per person, up to once a month)


【Growth Support】

・Server cost assistance (up to 10,000 yen per month, available to engineers)

・Book purchase support

・External training course fees reimbursement


【Life Events and Family Support】

・Parental and caregiving leave (available after the end of the probationary period)

・Marriage congratulatory gift (50,000 yen), childbirth congratulatory gift (100,000 yen)

・Relocation assistance


【Others】

・Comprehensive social insurance coverage (employment, workers' accident, health, welfare pension)

・Provision of company PCs

・Paid for medical checkups and gynecological examinations

・Company-wide recognition per quarter (Q)


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