Machine Learning Engineer | Food EC Service

【ABOUT THE COMPANY】

Sale of safe foods and food ingredients, such as organic vegetables, specially cultivated agricultural products, and additive-free processed foods, to the general public through websites and catalogs.

In 2017, two companies merged their businesses, and in 2018, another company was added to create a group. The company is taking a leap forward in a sustainable society by providing a service that allows many people to enjoy a better diet and by creating a system that rewards and makes producers of good food proud.

The company's main business area is a value-propositioned food e-commerce business, such as meal kits that meet the needs of busy customers, such as organic and specially cultivated fresh food, processed food with minimal additives, and other products that are safe and secure. In addition, they are solving social issues related to food through our business, such as wholesale of foodstuffs to nursery schools, consulting and media business using our e-commerce know-how, and mobile supermarkets that serve as infrastructure for living in depopulated areas.

Now that the company has entered its second decade of business, it will continue to provide a better dietary life for producers and customers through new initiatives and tricks, such as strengthening the products and services of each brand, establishing a new large-scale distribution center, and building a logistics system.

【JOB DESCRIPTION 】

《Responsibilities》
At the company, they are advancing the resolution of business challenges using technologies such as data science to address societal food issues with data. The Data Management Office (DMO) is responsible for the company-wide application of technologies such as machine learning, generative AI, and optimization. Therefore, the team handles the end-to-end process of machine learning model development, operation, and implementation. The Machine Learning Engineer will lead the requirements definition, development, and implementation of model development based on engineering best practices.

《Technical Environment》
・ML Platform: SageMaker
・Model Implementation: PyTorch
・Data Warehouse: Snowflake
・ETL: dbt
・Orchestration: Airflow
・CI/CD: GitHub Actions
・IaC: Terraform
・Source Code Management: GitHub, GitLab
・Communication Tool: Slack

《Position Highlight》
・Become central to the company's transformation through data utilization.
As evidenced by their growth strategy of "providing food that is good for both the planet and people through the power of business models and technology," data utilization is a pressing management issue for the company. The Machine Learning Engineer will play a central role in evolving products using technologies such as machine learning, generative AI, and optimization.

・Involve yourself in launching a new organization.
The company is establishing a company-wide data utilization organization to embed their rebuilt information utilization infrastructure into the business and further improve it. While they are already driving product evolution, mainly in the core business areas of demand forecasting and recommendations, there is a wealth of ideas for creating even better products. They are seeking members to join them in launching the organization that will realize these ideas and collaboratively advance the evolution of services that solve food-related challenges.

・Environment where you can focus on work output and develop your technical skills.
Remote work is available, allowing you to work from the location where you can concentrate best. Additionally, with a discretionary labor system that has no core time, you can focus on delivering the required output. Side jobs are permitted, enabling you to gain diverse experience by participating in other companies' projects, which can enhance your skills as an engineer. Within the company, study groups for data science and data engineering are also held, creating an environment where employees can learn from each other and share knowledge.

・Gain experience in implementing models utilizing a wide variety of data.
The company plays a role in directly connecting producers and consumers, and in doing so, possesses all the data related to producers, consumers, and the logistics in between. This includes not only structured data but also various forms of data such as images and text. Furthermore, besides the Oisix business, they have numerous other ventures, including B2C businesses like Radishbo-ya, Daichi wo Mamoru Kai, Purple Carrot, ISETAN DOOR, and d-Meal Kit, as well as B2B businesses such as food delivery for childcare facilities. The requirements for model operation are also diverse across these businesses. You will gain experience implementing models that leverage this wide array of data.

《Key Job Responsibilities》
・Business implementation of AI/ML.
・This includes not only the development of machine learning pipelines, models, and production code, but also requirements definition and post-implementation operation.
・Improving the productivity of machine learning model development and operation processes.

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【Welfare】
Full social insurance
Commuting allowance
Medical checkup
Remote work and shortened hours on request
　※Many mommy and daddy employees also work there.
Sidelines OK
Clothing optional
Employee discounts are available
Two days off per week (Saturday and Sunday)
※Depending on the situation, you may be required to work either Saturday or Sunday, but you will be asked to take a day off.
There is a space for napping
Free space (free to use for lunch and rest)

【Holidays】
Saturday/Sunday/National Holiday
Annual Paid Leave
New Year Holiday
Parental Leave
Nursing Care Leave
Congratulations & Condolence Leave

《Required》
・3+ years of Python application development experience (using Git, Docker, etc., regardless of whether it's an ML application).
・1+ year of experience using cloud platforms (AWS/GCP).
・Basic knowledge of machine learning preprocessing and algorithms, etc.
・Agile development experience in MLOps and DevOps.
・1+ year of experience in developing, implementing, and practically operating machine learning models.
・An attitude of being interested in the business, actively engaging in operations/practical tasks, and trying to understand how the business works and where its challenges lie.
・Communication skills enabling smooth communication with related departments.
・Self-motivation and curiosity to independently research and implement new technologies not used before.
・English reading comprehension sufficient to follow the latest AI/MLOps trends.
・Ability to appropriately judge the feasibility of introducing technology, considering both the impact of technology and business needs.
・Business-level or higher Japanese proficiency (JLPT N2 or above).

《Preferred》
・Ability to empathize with the company's mission of solving food-related challenges.
・Experience independently leading the business implementation and steady operation of machine learning models.
・Experience in defining requirements for AI/ML projects.
・Experience in interviewing business stakeholders about their challenges and proposing solutions.
・Cloud certification holder (e.g., AWS Certified Machine Learning).
・Deep knowledge of machine learning preprocessing and algorithms, etc.
・Track record in competitive programming competitions such as AtCoder.
・Award-winning experience in data science competitions such as Kaggle.