株式会社GA technologies

不動産およびM&A領域でテクノロジーを活用したイノベーションを推進する企業。AIやデータ分析を駆使し、RENOSYやITANDI BBなどのサービスを通じて、不動産取引の効率化と顧客体験の向上を実現。国内外で事業を展開し、業界全体のデジタル化を牽引している。

従業員数
837
設立年数
13年目
評価額
503億円
累計調達額
-
タグ
不動産
AI
DX
本社所在地
東京都港区六本木3-2-1 住友不動産六本木グランドタワー40階
設立
2013年03月
資本金
73億7,296万6,541 円(2024年10月末日時点)

株式会社GA technologies
Data / Applied ML / MLOps Engineer (Contract)の求人

ML Engineers to drive real estate business growth through AI and data analytics

募集概要

# About the Business & Hiring Background Our company is driven by the mission: “Creating a world-leading company that inspires people through technology and innovation.” We aim to provide services that enhance security and convenience, particularly in the traditionally legacy-driven real estate sector. Currently, we operate two main businesses: ・RENOSY Business – Focused on investment real estate transactions, our core business since inception. ・ITANDI Business – Providing SaaS solutions specialized in optimizing real estate business processes. To further expand our business, we are actively recruiting talent who can leverage data and technology to create new customer value. # Job Overview You will contribute to the growth of the RENOSY Business by agile development and stable operation of AI/ML from various internal and external data. Key Responsibilities ■ Development and Operations with MLOps ・Using workflow orchestration tool (airflow) migrate old ML models and create new ML models for business ・Utilising best practices in MLOps, building and maintainig new systems for data science support ・Supporting LLMOps on Dify with onboarding new services and creating workflows as needed ■ Machine Learning ・Create new Machine learning models for business requirements and business support such as predictive modeling and recommendation # Job Rewards & Opportunities ・As the business rapidly expands, the importance of data is increasing, allowing you to work in an environment where your contributions directly impact business growth. ・You will gain experience in managing a data platform with diverse applications, as many team members utilize data for BI and AI initiatives. ・With the business expanding globally and through M&A, you will have the opportunity to work with data beyond the domestic real estate sector. ・As part of an organization reporting directly to the CDO, you will have significant autonomy and the opportunity to take on various technical challenges in a fast-paced decision-making environment. # Analysis Environment ・Programming Languages: Python, SQL, Shell Script ・Development Environment: GitHub, AWS, Snowflake, Kubernetes, Docker ・Tools: Slack, Confluence, Backlog # Team 1 General Manager 3 Members

必須スキル

・Practical experience in deploying models in production. (both batch and real time inference) ・Machine learning model development using Python ・Experience in collaborative development using Git

歓迎スキル

・Expertise in machine learning and production level development ・Backend development experience using Python (e.g., developing APIs for machine learning models) ・Knowledge of tools such as Treasure Data, Snowflake, Mlflow, Airflow, Kubertnetes

求める人物像

・Strong self-management skills (ability to meet deadlines and communicate proactively) ・Passion for coding (commitment to writing clean and well-structured code)

応募概要

給与

1 person/month: Upto 800,000 yen ~ negotiable

勤務地

Tokyo Head Office (fully remote work available) You can come to the office, but please note that transportation costs will not be reimbursed. ▍Tokyo Head Office Sumitomo Fudosan Roppongi Grand Tower 40th floor 2-1 Roppongi 3-chome, Minato-ku, Tokyo 106-6290 Tel. 03-6441-3954 ▍Access ・Directly connected to Roppongi 1-chome Station on the Namboku Line ・5-minute walk from Roppongi Station on the Toei Oedo Line and Hibiya Line ・8-minute walk from Tameike-sanno Station on the Namboku Line and Ginza Line ・10-minute walk from Kamiyacho Station on the Hibiya Line

雇用形態

Contract

勤務体系

Work anytime. No late night or early morning compensation. Please discuss the working style as per need

試用期間

福利厚生

更新日時:

2025/04/02 08:10


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