Collaborate with cross-functional teams to design, develop, and implement AI features, focusing on areas like natural language processing, data analysis, and predictive modeling.
Collaborate with cross-functional teams to design, develop, and implement AI features, focusing on areas like natural language processing, data analysis, and predictive modeling.
Develop backend services for AI features: Build and maintain scalable APIs and microservices in Java (Spring Boot) or Python that expose our generative AI capabilities - routing user queries to LLMs and other models, processing data, and returning results securely and efficiently.
Leading the development and implementation of innovative and strategic projects to develop highly scalable AI solutions within our global AI@BE program in alignment with business objectives and operational needs
Lead a team of young and bright MLOps Engineers in conducting research, design, and prototype MLOps practices, tools, and frameworks to expedite the machine learning lifecycle at MoneyLion.
Improve the basic search quality and user experience: Optimize query analysis and text relevance matching. Understand e-commerce video content and implement multi-modal matching. Improve users' perception of product authority, and deeply participate in the design and implementation of core search products. Comprehensively improve the end-to-end shopping experience from browsing to after-sales.
Currently pursuing PhD in Computer Science, AI, Mathematics, or a related technical discipline, with a strong foundation in data structures, algorithms, and mathematical modeling.
Grounded in a talent-centric mindset, Maker Lab is a marketing agency designed to build decentralised technology-led agency teams, rooted in collaboration with clients from the ground up. Maker Lab’s cross-functional teams of multidisciplinary specialists are embedded into client teams across digital marketing competencies from measurement & analytics to content production.
Collaborate with stakeholders to define and document go-to-market plans across the full product portfolio spanning physical retail and e-commerce channels.
Build global product catalog and content understanding systems, modeling products, videos, images, merchants, and brands with structured and semantic representations.
Responsible for using algorithms to mine, identify, and predict risks and low-quality merchants, products, and creators in e-commerce scenarios, and assist businesses in managing and controlling them.
Build global logistic and warehousing network, improve operations efficiency and reduce operational cost with data analysis, machine learning and operation research methods.
Improve the basic search quality and user experience: Optimize query analysis and text relevance matching. Understand e-commerce video content and implement multi-modal matching. Improve users' perception of product authority, and deeply participate in the design and implementation of core search products. Comprehensively improve the end-to-end shopping experience from browsing to after-sales.
Participate in building large-scale (10 million to 100 million) e-commerce recommendation algorithms and systems, including commodity recommendations, live stream recommendations, short video recommendations etc.
Responsible for the computational performance optimization of ByteDance's recommendation mid-platform models, conduct in-depth tuning for inference/training bottlenecks in business scenarios, and improve computing utilization.