スキルハウスの採用情報
Machine Learning Engineer (Recommendation Systems)
役職：
Machine Learning Engineer (Recommendation Systems)
雇用形態:
正社員
給与:
12000000.00
勤務時間:
Japanese Level - None,English Level - Fluent (TOEIC 990)
職務内容
A Global IT Service firm is looking for a passionate Machine Learning Engineer who will help build and scale recommendation and personalization systems by contributing to the development and deployment of ML solutions into production.
You will support the design and implementation of end-to-end model and data pipelines (feature creation, training, evaluation, and serving), working closely with senior engineers and cross-functional partners to deliver reliable, measurable improvements across business units.
Responsibilities:
- Build & Scale ML Pipelines: Design, develop, and maintain robust end-to-end ML pipelines for Rakuten’s recommendation and personalization platform - covering data generation, training, evaluation, deployment - with a focus on reliability, scalability, and maintainability
- Deep Dive into Models & Data: Develop a strong understanding of data sources, feature definitions, and model behavior to identify gaps in data quality, feature coverage, online/offline consistency, and system latency - and implement improvements that better align platform performance with business needs
- Enable Business Value through ML: Deliver production-grade models and reusable ML components (e.g., feature sets, embeddings, ranking services), with clear documentation and measurable outcomes, to accelerate adoption and business impact across multiple business units
- Collaborate Across Teams: Partner closely with Business Units (BUs), data scientists, data engineers, analytics, and product teams to define use cases, translate requirements into ML solutions, and deliver effective data pipelines and deployable models
- Plan and Deliver: Prioritize and manage ML engineering work across new development and operations (e.g., model retrains, monitoring/alerting, incident response, backfills, A/B test support, and production releases) to meet platform SLAs and ensure continuous improvement
Required skills:
- More than 3 years of hands-on experience in Machine Learning Engineering / Applied ML / MLOps (or closely related software engineering roles), including building, deploying, and operating ML pipelines in production
- Demonstrated experience with ML fundamentals and workflows, such as feature engineering, model training/evaluation, and production inference (batch and/or real-time)
- Excellent communication skills, with the ability to clearly explain technical concepts and trade-offs to both technical and non-technical stakeholders
- Proven ability to work effectively in a collaborative, cross-functional environment (e.g., partnering with software engineers, data scientists, data engineers, analysts, and product managers)
Why should you apply:
- Great opportunity to be able to work for well-established company
- Collaborate with a highly international team across Japan and Europe, using English as the primary working language
- Drive measurable business impact by building AI-powered personalization solutions that improve user engagement and growth
Company Overview: This is a global company with a strong presence in multiple business sectors. It has achieved sustained growth both domestically and internationally, including in the U.S. and Europe. The company prides itself on its diverse and international environment, providing ample career opportunities and a commitment to equal opportunity. With a wide range of business activities, the company also works with various technologies. You can choose your preferred working environment, whether Windows or Mac! Meals at the employee cafeteria are free, and the chef regularly comes up with new menus, ensuring you never get bored of the meals!
Work Hours: 9:00 AM – 5:30 PM (Flextime or staggered working hours possible)
Work Style: Hybrid (Typically 4 days in the office, 1 day working from home)
Holidays: Saturdays, Sundays, public holidays, New Year holidays, paid leave, bereavement leave, and other special leave
Benefits: Full social insurance (employee pension insurance, health insurance, worker’s accident compensation insurance, unemployment insurance), DC pension plan, transportation allowance, childcare and caregiving support, cafeteria, retirement benefit system, welfare services (Relo Club), health counseling services, relocation support (visa support, moving), employee discounts (moving, language classes, etc.), and more
Interview Process: 3~4 times
