SmartNews
information and news discovery
StafforSeniorStaffMachineLearningEngineer,RecommendationAlgorithm
“Staff or Senior Staff Machine Learning Engineer, Recommendation Algorithm at SmartNews. Skills: recommendation ecosystem, ranking strategies, Foundation Models, LLMs, scalable recommendation solutions, multi-task learning frameworks, SOTA techniques. Define and drive the technical roadmap for vertical ranking. Lead the design and implementation of highly scalable, low-latency ranking systems and multi-task learning frameworks”
What You'll Achieve.
drive user engagement and revenue growth; unlock new levels of user value; driving sustainable business growth and industry-leading user experiences; aligning machine learning initiatives with global business priorities and long-term product vision; translating high-level business objectives into rigorous technical requirements and measurable KPIs; ensure robust, data-driven decision-making; optimize engagement, retention, and monetization; deliver measurable results; continuously refine performance and elevate the quality of recommendations for our users; contributes to strengthening both vertical strategies and the broader recommendation ecosystem; turn data into impact
Industry & Context.
Strategic Problem Solving; take ambiguous business challenges and decompose them into actionable, high-impact technical workstreams; solve complex optimization problems
What They're Looking For.
Must Have
5-10+ years of experience in applied machine learning, with a focus on large-scale recommendation systems, ranking, or computational advertising, Demonstrated ability to take ambiguous business challenges and decompose them into actionable, high-impact technical workstreams, Mastery of deep learning architectures (e.g., Transformers, MoE, Embeddings) and their application in production environments at scale, Extensive experience in designing and scaling complex ML pipelines, from data ingestion and feature engineering to online inference and monitoring
Nice to Have
track record of contributions to the ML community (e.g., publications in KDD, RecSys, NeurIPS, or significant open-source contributions), Deep understanding of distributed computing frameworks (Spark, Ray) and high-performance serving infrastructures, Experience with user growth loops, monetization strategies, and the economics of content platforms, Experience working in multi-national tech companies, navigating different market dynamics and organizational structures, At least professional working proficiency in Japanese language
What You'll Do.
Define and drive the technical roadmap for vertical ranking
Lead the design and implementation of highly scalable
low-latency ranking systems and multi-task learning frameworks
Spearhead the adoption of SOTA techniques (e.g.
Reinforcement Learning
Graph Neural Networks)
Drive the evolution of our experimentation culture
overseeing complex A/B testing strategies and offline-to-online correlation analysis
How You'll Work.
Team & Collaboration
Partner closely with Product and Business teams to design and deploy scalable recommendation solutions; Collaborate directly with Product and Business teams to identify high-impact opportunities; Act as a strategic partner to Product and Business Directors; Collaborating cross-functionally
Communication Scope
Exceptional stakeholder management skills, with the ability to influence technical and non-technical audiences
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