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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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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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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Participate in building a large-scale graph storage and graph learning platform to improve relationship building and governance within the e-commerce community.
Explore and research cutting-edge technologies in machine learning/graph learning/sequence learning and related fields, implement these technologies in practical business scenarios, and support the production of scalable and optimised machine learning models.
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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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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Work in a cross-functional team setting to mitigate business risks.
Work with relevant software platform to develop/deploy/monitor the models.
Individuals who are completing or have recently completed a Bachelor's degree or Master's degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
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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.
Individuals who are completing or have recently completed a PhD degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
...
Participate in building a large-scale graph storage and graph learning platform to improve relationship building and governance within the e-commerce community.
Explore and research cutting-edge technologies in machine learning/graph learning/sequence learning and related fields, implement these technologies in practical business scenarios, and support the production of scalable and optimised machine learning models.
Individuals who are completing or have recently completed a PhD degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
...
Work in a cross-functional team setting to mitigate business risks.
Work with relevant software platform to develop/deploy/monitor the models.
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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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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As an internal platform serving multiple teams, plan and optimize the utilization of large volumes of heterogeneous resources across multiple hardware generations, data centers, service tiers, and resource pools. Develop automated and dynamic optimization strategies based on changes in model size, service traffic, and workload characteristics.
Bachelor's degree or above in Computer Science, Software Engineering, or a related field
Proficient in C++ and Python programming in Linux environments.
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Collaborate with the business and algorithm teams to identify performance issues, provide full stack performance analysis, bottleneck diagnosis, and optimization solutions, consolidate general-purpose performance optimization components, toolchains, and platform capabilities, and empower multiple internal business.
Individuals who are completing or have recently completed a Bachelor's/ Master's degree in computing or a related discipline.
Familiar with mainstream model compilation stacks (such as TVM, MLIR, XLA, etc.), with relevant experience in development, and optimization;
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