Staff Or Senior Staff Machine Learning Engineer, Recommendation Algorithm

SmartNews Machine Learning Engineer Opportunity

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, 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.