Design and build supporting/debugging tools as needed.
Support the production of scalable and optimised AI/machine learning (ML) models.
Focus on building algorithms for the extraction, transformation and loading of large volumes of realtime, unstructured data to deploy AI/ML solutions from theoretical data science models.
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Responsible for the development of deep learning and operations research models and related intelligent systems for the supply chain and logistics of the global E-Commerce business.
Pioneer the development of domain-specific LLMs by leveraging massive e-commerce data for Continual Pre-Training (CPT), Supervised Fine-Tuning (SFT), and Reinforcement Learning (RL). Design and deploy intelligent AI Agents based on an "Agent + Skill" framework to autonomously diagnose and resolve complex user-facing and operational issues.
Utilize e-commerce big data and deep learning models to predict end-to-end estimated time of arrival (ETA), and some logistics events such as failed delivery, delivered but not received to enhance the user logistics experience. Build logistics network knowledge graphs and predict the spatio-temporal trajectory sequence of express packages through deep learning, statistical inference and other algorithmic methods. Use NLP and LLM algorithms to handle address problems such as address verification and address suggestion.
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Participate in the exploration and development of personalized AI search, with a focus on harness engineering, post-training optimization, and rubric-based automated evaluation, to build next-generation search experiences that better understand users, reason over intent, and make intelligent decisions.
Work in a team setting and apply knowledge in statistics, scripting and programming languages required by the firm.
Work with the relevant software platforms in which the models are deployed.
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Construct multimodal semantic links across video-product, product-product, and video-video relationships to support trend understanding, product mining, AIGC generation, and content-commerce supply optimization.
Explore next-generation generative search and recommendation through full-format representation learning and SID modeling across videos, livestreams, products, and queries.
Design and develop generative algorithms tailored for high engaging, high conversion e-commerce visual creatives, solving challenges in identity-preserving and aesthetic style consistency to produce production-grade intelligent background synthesis,virtual try-on, and localised lifestyle scene generation.
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Problem Solving for Governance Applications: Address challenges such as long text/sequence modeling, few-shot learning, content moderation, violation detection, and policy recommendation using large models and multimodal approaches.
Model Development and Optimization: Research and optimize e-commerce-specific NLP and multimodal large models to improve multilingual, multi-task, and multi-modal algorithm performance across various e-commerce scenarios.
Individuals who are completing or have recently completed a PhD degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
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Explore the integration of LLMs / VLMs with recommendation systems to develop adaptive and evolving intelligent recommenders.
Research end-to-end generative recommendation and system optimization methods that balance efficiency and user experience.
Individuals who are completing or have recently completed a PhD degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
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Conduct market research and due diligence to support land, power, water, permitting, and other infrastructure assessments for new data center developments.
Analyze commercial data, project costs, and supplier performance to provide insights that support business and procurement decisions.
Coordinate with internal stakeholders and external partners to support contract management, commercial negotiations, and project execution.
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