Staff or Senior Staff Machine Learning Engineer (Recommendation Systems)

TL;DR

Staff or Senior Staff Machine Learning Engineer (Recommendation Systems): Designing and scaling machine learning systems for personalized news discovery with an accent on vertical ranking and large-scale recommendation solutions. Focus on integrating Foundation Models and LLMs into the product DNA and driving sustainable business growth through SOTA ML execution.

Location: Hybrid; Must be based in or be able to relocate to Tokyo, Japan

Company

hirify.global is a global information and news discovery company utilizing unique machine-learning technology to deliver quality news to millions of users.

What you will do

• Define and drive the technical roadmap for vertical ranking aligned with global business priorities and long-term product vision.
• Lead the design and implementation of scalable, low-latency ranking systems and multi-task learning frameworks.
• Collaborate with Product and Business Directors to translate high-level objectives into rigorous technical requirements and KPIs.
• Mentor senior talent and establish engineering best practices for model lifecycle management (MLOps).
• Spearhead the adoption of SOTA techniques, including LLM-based ranking, Reinforcement Learning, and Graph Neural Networks.
• Oversee complex A/B testing strategies and offline-to-online correlation analysis to ensure data-driven decision-making.

Requirements

• 5-10+ years (Staff) or 10+ years (Senior Staff) of experience in applied ML, focusing on large-scale recommendation systems, ranking, or computational advertising.
• Mastery of deep learning architectures (Transformers, MoE, Embeddings) in production environments at scale.
• Extensive experience designing and scaling complex ML pipelines from data ingestion to online inference and monitoring.
• Proven ability to decompose ambiguous business challenges into actionable, high-impact technical workstreams.
• Exceptional stakeholder management and communication skills for influencing both technical and non-technical audiences.
• Visa sponsorship and overseas relocation support available for eligible candidates.

Nice to have

• Contributions to the ML community via publications (KDD, RecSys, NeurIPS) or significant open-source contributions.
• Deep understanding of distributed computing frameworks like Spark and Ray.
• Professional working proficiency in Japanese.
• Experience with user growth loops, monetization strategies, and content platform economics.

Culture & Benefits

• Full healthcare and social insurance as required by Japanese labor law, including annual health checks.
• Comprehensive visa sponsorship and overseas relocation support for eligible candidates.
• A high-ownership environment where every model is evaluated against clear business metrics.
• Opportunity to work at the intersection of business impact and SOTA ML innovation.