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Descripción del puesto:
Our team aims to apply LLM/Agent technology to our recommendation system and Agent Auto Quality Assurance, thereby improving service satisfaction and efficiency for chatbots and agents. Your scope will include, but not be limited to:
* Generative RecSys: Design and develop core components of the chatbot's recommendation, adopting the thought of a generative model (e.g. LLM reasoning/scaling law) to improve CTR of RecSys.
* Proactive Support Agents: Modeling user's CS behaviour based on user profiles and historical interaction data to recognise users' real intent and answer it proactively.
* Feature Insight Agents: Automatically reason potential features and defining user's event from Agent-Human dialogues.
* AutoQA Agent: Build an in-domain LLM with SFT for long context and design memory context management to check the agent service quality automatically
Requerimientos del candidato/a:
* Currently pursuing a Bachelor's degree or above in Computer Science, Artificial Intelligence, or a related discipline.
* Solid experience with optimisation of end-to-end RecSys, including retrieval-ranking systems, Deep Learning RCMD (e.g., xDeepFM, DIN, MMoE), as well as LLM-based generative recommendation models (e.g., HSTU, OneRec, RankMixer).
* Proficient in Python and experienced with deep learning frameworks such as PyTorch or TensorFlow.
* Strong analytical and problem-solving abilities, with a passion for building intelligent, user-centric products.
* Experience in training and fine-tuning large language models using techniques such as supervised fine-tuning (SFT) or reinforcement learning (RL).
* Prior experience developing or optimising algorithms for large-scale recommendation, search, or advertising systems.
* Experience in chatbot algorithm development is a strong plus
We are the Customer Service Chatbot team at Shopee Singapore, committed to developing multilingual, intelligent dialogue systems that serve a wide range of consumers and sellers. Our focus lies in applying advanced AI technologies - including recommendation systems, Large Language Models (LLMs), autonomous agents, and reinforcement learning - to customer service scenarios, continuously enhancing interaction quality and user experience
| Origen: | Web de la compañía |
| Publicado: | 25 Feb 2026 (comprobado el 10 Mar 2026) |
| Tipo de oferta: | Prácticas |
| Sector: | Internet / Nuevos Medios |
| Idiomas: | Inglés |
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