Design and develop ML products to be integrated with Treasure AI's Customer Data Platform (CDP).
Own technical areas, drive ML product projects, track progress, and mitigate risks with cross-functional teams (PMs, UX, architects, engineers).
Define system architecture for ML products and implement components to enhance user experience.
Design and implement scalable ELT data pipelines while managing the ML lifecycle (training and inference).
Solve technical problems and meet ML product objectives in ambiguous environments; participate in on-call production support.
Promote and enforce best practices: ML research methodologies, coding standards, code reviews, source control, testing, release, and operational excellence.
技術スタック
必須スキル
Python and core ML ecosystem (NumPy, Pandas, Scikit-learn, PyTorch)
ML production systems knowledge; end-to-end ML lifecycle and ML pipeline development
Data engineering fundamentals; design, deployment, and operation of scalable ML systems
Public cloud experience, specifically AWS
Strong English communication; cross-functional collaboration across time zones
歓迎スキル（該当する場合）
Security design principles and best practices
Big data technologies (Hive, Trino, Spark, BigQuery, Redshift)
Open source contributions
キャリア成長観点
End-to-end ML productizationとスケーラブルなAI基盤の設計・運用を通じ、技術とビジネス価値を橋渡しするリーダーシップが身につく。