Staff or Senior Staff Machine Learning Engineer, Recommendation Algorithm

About SmartNews 

SmartNews is a leading global information and news discovery company dedicated to delivering quality information to the people who need it. Thanks to our unique machine-learning technology and relationships with more than 3,000 global publisher partners, we provide news that matters to millions of users.

Founded in 2012 in Tokyo, SmartNews also has offices in Osaka (Kansai Office), Palo Alto, New York and Singapore.

If you share our vision and are passionate about our mission, we encourage you to apply!

The Team

The Vertical Ranking Team builds the machine learning systems that power personalized experiences across SmartNews. We partner closely with Product and Business teams to design and deploy scalable recommendation solutions, understandings that drive user engagement and revenue growth across key surfaces such as For You, Follow Recommendations, Search, Ads, and scale the emerging New Era products.

Your Role

As a Staff or Senior Staff Machine Learning Engineer, you will be the primary technical architect and strategic partner driving the evolution of SmartNews’ recommendation ecosystem. Your mission is to bridge the gap between ambitious product visions and state-of-the-art ML execution. You won't just build models; you will define the growth engine of our product.

You will collaborate directly with Product and Business teams to identify high-impact opportunities, transforming business goals into sophisticated ranking strategies. In this "AI-transformative" era, you will lead the charge in integrating Foundation Models and LLMs into our product DNA to unlock new levels of user value. Beyond technical delivery, you will be a force multiplier—mentoring senior talent and ensuring our ML roadmap is fundamentally aligned with driving sustainable business growth and industry-leading user experiences.

Your Responsibilities

• Technical Strategy & Roadmap: Define and drive the technical roadmap for vertical ranking, aligning machine learning initiatives with global business priorities and long-term product vision.
• Architectural Leadership: Lead the design and implementation of highly scalable, low-latency ranking systems and multi-task learning frameworks that handle massive-scale user behavior data.
• Cross-functional Influence: Act as a strategic partner to Product and Business Directors, translating high-level business objectives into rigorous technical requirements and measurable KPIs.
• Mentorship & Talent Development: Cultivate a high-performing engineering culture by mentoring junior to senior engineers, conducting deep-dive design reviews, and establishing best practices for model lifecycle management (MLOps).
• Advanced ML Innovation: Spearhead the adoption of SOTA techniques (e.g., LLM-based ranking, Reinforcement Learning, Graph Neural Networks) to solve complex optimization problems across Search, Ads, and Personalized Feeds.
• Experimentation & Excellence: Drive the evolution of our experimentation culture, overseeing complex A/B testing strategies and offline-to-online correlation analysis to ensure robust, data-driven decision-making.

Requirements

Minimum requirements

• Proven Track Record: 5-10+ years (Staff) or 10+ years (Senior Staff) of experience in applied machine learning, with a focus on large-scale recommendation systems, ranking, or computational advertising.
• Strategic Problem Solving: Demonstrated ability to take ambiguous business challenges and decompose them into actionable, high-impact technical workstreams.
• Technical Depth: Mastery of deep learning architectures (e.g., Transformers, MoE, Embeddings) and their application in production environments at scale.
• Leadership & Communication: Exceptional stakeholder management skills, with the ability to influence technical and non-technical audiences. 
• System Design: Extensive experience in designing and scaling complex ML pipelines, from data ingestion and feature engineering to online inference and monitoring.

Nice to have experiences/skills

• Industry Recognition: Strong track record of contributions to the ML community (e.g., publications in KDD, RecSys, NeurIPS, or significant open-source contributions).
• Infrastructure Expertise: Deep understanding of distributed computing frameworks (Spark, Ray) and high-performance serving infrastructures.
• Full-stack Perspective: Experience with user growth loops, monetization strategies, and the economics of content platforms.
• Global Experience: Experience working in multi-national tech companies, navigating different market dynamics and organizational structures.
• Japanese language: At least professional working proficiency

Role Highlights

Our work sits at the intersection of business impact and ML innovation. We translate product requirements and strategic priorities into high-performing ranking strategies that optimize engagement, retention, and monetization. From feature design and model development to experimentation and online iteration, we play a critical role in evolving and enhancing the recommendation pipeline to deliver measurable results.

We operate in a fast-moving environment where real-world impact matters. Every model is evaluated against clear business metrics. By leveraging large-scale behavioral data, advanced modeling techniques, and rigorous A/B testing, we continuously refine performance and elevate the quality of recommendations for our users.

Our team values strong ownership and accountability. Each initiative is grounded in data, aligned with business goals, and contributes to strengthening both vertical strategies and the broader recommendation ecosystem.

If you’re passionate about applying machine learning to solve meaningful business challenges, shaping recommendation strategies that directly influence growth, and collaborating cross-functionally to turn data into impact, the Vertical Ranking Team offers a unique opportunity to drive results at scale.

Related Links

• Click here or visit our careers site to check employee interviews.

Working condition

• Office Location: Tokyo
• Click here or visit our careers site for more info.

Benefits

Benefits available at the SmartNews Tokyo Office

• All healthcare and social insurance required by the Japanese labor law, plus annual health check
• Visa sponsorship and overseas relocation support available for eligible candidates
• Click here or visit our careers site for more info about our benefits.