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Senior Machine Learning Engineer

Publication date 2024/02/28

Work Location , Expected Annual Income :

Tokyo,7.0M ~ 13.0M

About the Company :

Leading Fintech Company (biggest market share Japan)

Responsibilities :

Shibuya based, fintech start with million of user daily. Actively enhancing its organizational structure of engineering utilizing AI and Machine Learning technology for major products and services (B2B and B2C). Its personal financial management services include economic media that conveys money related themes, automatic savings app and mirai talk channel where customers can resolve their financial concerns together directly with financial planners. Its Cloud services comprise cloud accounting software, cloud-based tax return, invoice preparation software, payroll calculation, and cloud-based payment reconciliation.

"We strive to realize our vision of "becoming everyone's 'money platform'" through various products and services, including those for individual and corporate customers, to promote more effective use and analysis of data and solve customers' issues. We are looking for people who can promote the development of features and problem-solving by applying machine learning in cooperation with the product development organization to address the issues of the company many products and services."


- Proposal, evaluation, development, and operation to solve issues for each of Money Forward's services and products using machine learning
- Support the development of machine learning features and processes for each company's product development teams
- Collaboration with data analysts, analyst engineers, and data engineers, including the Analytics Promotion Office, - Analytics Infrastructure Department, and Money Forward Lab, to create a foundation for data-driven analysis and decision making
- Creating business value through the development of machine learning infrastructure based on a company-wide data strategy

Benefits :

Advantages of this position:

 The attractive aspect of this position is that you will be able to work on providing additional value and developing features through machine learning by utilizing data from a wide variety of products and services, from accounting and back-office services for corporations to services for individuals. Furthermore, in cooperation with the respective product teams and PdMs, you can lead the development features as ‘user-first‘ from the idea discussion and technical evaluation stage.

You will have broad authority in this position to collaborate with product development teams and launch new development projects. You will be able to develop your career and experience as the organization grows.

 In addition to developing your technical expertise as a technical lead, you will be able to realize a variety of career paths, such as taking on team management as the organization expands.

There are great opportunities for growth, including the ability to expand the scope of your role to include organizational structure, technical infrastructure, infrastructure development, and data management.

Culture fit and mindset:

- People who respect Money Forward's mission, vision, and values
- People who envision the potential in Money Forward's data
- People who have the communication skills to make decisions on technology selection and policies through open discussions and leadership skills to lead the team.
- People who have a habit of continuous learning constantly update their skills and knowledge, proactively share their expertise and achievements with the team, and are happy to see growth for themselves, the organization, and the team.
- People who can actively communicate across organizational boundaries and can solve complex inter-organizational issues.
- People who find pleasure and satisfaction in solving business problems with machine learning technology.

Technology Stack:
- Machine Learning: Jupyter Notebook, SageMaker, TensorFlow, PyTorch, etc.
- AWS: SageMaker, EKS, ECS, Lambda, Step Functions, etc.
- GCP: Big Query, GKE, etc.
- Development languages: Python, Go, etc.

Tools used:

- Business efficiency: GSuite
- Repository management: GitHub
- CI/CD: CircleCI, bitrise, Argo CD, CodeBuild, GitHub Actions
- Development environment: Vagrant, Docker, Terraform Enterprise
- Monitoring: Datadog, Rollbar, Bugsnag, Sently, New Relic
- Communication: Slack, Chatwork
- Ticket management: Jira, Asana, Trello, Backlog
- Security and Automation: OWASP ZAP, Burp Suite, Sider (Brakeman), Snyk, Vaddy, Dockle, Trivy

Required Experience / Abilities / Skills :


- 3+ years of experience implementing machine learning algorithms, learning and improving models, and implementing and developing them into production services
- Deep understanding of machine learning frameworks (PyTorch, TensorFlow, etc.)
- Broad knowledge of the machine learning field, including conventional statistical machine learning methods and deep learning models (computer vision, natural language processing, time series data analysis, mathematical optimization, etc.)
- Experience in designing and implementing effectiveness verification, including effectiveness testing, performance evaluation, and A/B testing in an online environment in a real-world service
- Experience working to improve the performance of machine learning models, including model refinement and fine-tuning
- Experience and understanding of software engineering (design documentation, understanding of software design review processes such as reviews, software development in distributed code repositories, and collaborative work such as pull requests, code reviews, etc.)
- Experience working in a global development team (experience in English communication, documentation, technical and code reviews, and other development tasks)

Language Requirement:

- English: Business-Level
- Japanese: Business-Level

Preferred skills and experience:

- Experience participating in and winning machine learning competitions such as Kaggle Master
- Domain knowledge of business areas, including accounting/back office and financial data
- Experience designing and developing modern backend architectures such as container (Docker, etc.), container orchestration (Kubernetes, ECS, etc.), and microservice architectures
- Experience building machine learning pipelines, workflows, and implementing systems (Kubeflow, MLFlow, etc.)
- Experience in designing, developing, and operating large-scale machine learning systems and managing development teams
- Deep understanding of team-based software development (experience with development projects using Scrum and Agile methodologies)
- Experience in security design, development, and operation of cloud infrastructure
- Knowledge of data security standards such as personal information, financial and accounting data handling, and PCI DSS, and experience designing, developing, and operating systems following these requirements.

Contact Information :

Agent Contact:

Gorni Alessio

JOB ID : IJB2003886

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