Machine Learning Engineer - Recommendation Department, AI & Data Division
Core
Build and scale Rakuten's recommendation and personalization systems to impact millions of users daily.
Role type
Machine Learning Engineer (Recommendation Systems)
Builds
End-to-end ML pipelines, production-grade models, and reusable ML components (feature sets, embeddings, ranking services) for Rakuten's ecosystem.
Domain
E-commerce / Recommendation Systems / AI
Deliverable
production ML models
Required skills
ML fundamentals, feature engineering, model training/evaluation, production inference (batch/real-time), MLOps, system latency optimization, cross-functional collaboration
Preferred skills
scikit-learn, PyTorch, CI/CD for ML, model registry, experiment design, A/B testing, SQL, Spark, Python
Technologies
scikit-learn, PyTorch, SQL, Spark, Python
Responsibilities
Design and maintain robust end-to-end ML pipelines; Develop data sources, feature definitions, and model behavior understanding; Deliver production-grade models and reusable ML components; Partner with BUs, data scientists, and product teams to define use cases; Prioritize and manage ML engineering work including model retrains, monitoring, and production releases.
Seniority
Mid-Senior, hands-on IC