Design and operate commercial real-estate software covering real-time data integration, domain modeling, AI/LLM features, security, and rapid product development. Remote work is available.
About this role
This role is part of the Real Estate AI Lab, launched in January 2025 to develop AI solutions for rental, sales, and urban development using real estate data and software. Current work includes rent valuation and real-estate-focused AI agents.
Responsibilities include collecting, analyzing, maintaining, and operating diverse real estate data; building ETL pipelines; data cleansing and feature engineering; and designing and operating data platforms and cloud infrastructure. The engineer researches and develops machine-learning and deep-learning models, selects and implements algorithms suited to the business domain, including regression, classification, and generative models, and tunes performance for online and batch inference. The role also involves researching and applying recent papers, open-source software, and large language models, and may include writing about the work.
Working with business team members, the engineer identifies AI use cases and needs, plans AI products, and leads development from proof of concept through minimum viable product. The role is expected to lead research and development of models as a data science and machine-learning specialist, while refining the questions to be solved through dialogue with the business team.
Required qualifications include basic software development skills; experience with team development using GitHub or similar tools; experience developing tools or applications with a scripting language; practical experience in data engineering or data analysis; experience using large-scale data processing platforms or cloud infrastructure such as AWS or GCP; experience analyzing data or building pipelines with SQL; knowledge of and implementation experience in machine learning and deep learning; experience developing models with Python and frameworks such as PyTorch, TensorFlow, or scikit-learn; understanding of basic algorithms and statistical methods; and business-to-native Japanese ability for communication with users and customers.
Experience with large language models such as ChatGPT, ChatGPT APIs and other models, MLOps environment construction, Docker or Kubernetes and CI/CD for machine learning, and data visualization or BI tools such as Tableau, Looker, or Power BI is welcomed. Experience developing in a startup or new business, or working at speed in a small expert team, is also welcomed.
The development environment includes Python, PyTorch, TensorFlow, scikit-learn, AWS, GCP, GitHub, GitHub Actions, Sentry, Datadog, JIRA, Slack, GitHub Copilot, Claude Code, Cursor, Devin, and Codex. The position is full-time with no fixed contract term and a three-month probationary period. The listed annual salary range is JPY 7,000,000–15,000,000; the final grade and amount are individually determined. Monthly pay includes a fixed allowance equivalent to 40 hours of overtime, with additional payment when applicable. Salary revisions and bonuses may each occur up to twice a year depending on company and individual performance.
The workplace is the headquarters in Akasaka, Minato-ku, Tokyo, with other company-designated locations possible. Commuting to the headquarters combined with remote work is recommended, and remote work is available. Working hours use a discretionary system, based on 10:00–19:00, with start and end times left to the worker; work beyond scheduled hours may occur. Holidays are Saturdays, Sundays, and public holidays, with 125 annual holidays, summer leave, Welcome leave, and year-end and New Year holidays. Benefits include flextime and discretionary work systems, rent and moving-expense subsidies, support for qualifications and book purchases, and company-paid study-meeting fees. Social insurance is provided, and a smoking room is installed.
This is an AI-generated summary of the employer's original posting — details can be incomplete, out of date or simply wrong. Always confirm everything on the official posting before applying.