Work closely with partner teams across the company and around the world.
Design and develop integrations with other systems across the big data ecosystem.
Individuals who are completing or have recently completed a Bachelor's / Master's degree in Computer Science, Engineering, Mathematics, Software Engineering, or a related technical discipline.
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Architecture for data at the scale of hundreds of billions: Conducting in-depth research and innovation in all aspects, from large-scale offline computing and performance and scheduling optimization of distributed systems to building high-availability, high-throughput, and low-latency online services.
Recommendation Technologies: Leveraging ultra-large-scale machine learning to build industry-leading search recommendation systems and continuously explore and innovate in search recommendation technologies.
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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Collaborate with cross-functional teams to deliver event data ingestion, transformation, and storage solutions that meet diverse business requirements.
Troubleshoot and resolve complex issues in production systems to ensure minimal downtime and optimal performance.
Individuals who are completing or have recently completed a Bachelor's / Master's degree in Computer Science, Software Engineering, or a related technical discipline.
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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.
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.
Utilize time series forecasting techniques to predict sales at different granularities and horizons, such as warehouse-level manpower forecasting, inventory-level demand forecasting etc. We need strong machine learning and deep learning skills to detect important factors and model the relationship between the future and history.
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Root cause analysis of heterogeneous data: Large models must automatically identify fault root causes and build knowledge from massive heterogeneous monitoring data, requiring high model understanding and generalization capability.
Technology implementation and adaptation: Hardware innovation must comply with policies and fit industry needs, while AI operations must integrate with existing platforms and tools. Successfully combining and implementing these poses significant challenges.
Solve key technical problems in data centers and increase global competitiveness.
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Optimize the web application performance, improve overall user experience.
Individuals who are completing or have recently completed a Bachelor's degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
Programming experience in JavaScript/TypeScript, HTML, CSS, python, web debugging toolchain.
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