Algorithm Engineer, Marketplace Intelligence

Department Engineering and Technology
- LevelEntry Level
- LocationSingapore

The Engineering and Technology team is at the core of the Shopee platform development. The team is made up of a group of passionate engineers from all over the world, striving to build the best systems with the most suitable technologies. Our engineers do not merely solve problems at hand; We build foundations for a long-lasting future. We don't limit ourselves on what we can or can't do; we take matters into our own hands even if it means drilling down to the bottom layer of the computing platform. Shopee's hyper-growing business scale has transformed most "innocent" problems into huge technical challenges, and there is no better place to experience it first-hand if you love technologies as much as we do.

**About the Team**:

- Shopee will be prioritizing applicants who have a **current right to work in Singapore**, and **do not require Shopee sponsorship of a visa**.
- Kindly note that you can only be considered in **one recruitment process at a time within Sea Group** and will be considered for jobs in the order that you have applied.

The Marketplace Intelligence and Data team's mission is to build sustainable and efficient data and intelligence products to facilitate Shopee's business development. The team is responsible for Shopee e-commerce data warehouse construction, merchant and operation data product construction, all-link traffic data, product algorithms, including product release, control, information optimization, SPU library and its comparison business, marketing algorithms, including Merchandising, Product Selection, Recommendation Algorithm, Evaluation Algorithms, User Profiling, and in addition, basic AI capabilities, such as Machine Translation, Speech Algorithm, Image Algorithm, and Real-person Authentication.

We are the Shopee Intelligent Customer Service Chatbot team based in Singapore, dedicated to exploring cutting-edge AI technologies, including but not limited to large language models (LLMs), natural language processing, deep learning, and knowledge graphs. Our mission is to tackle core challenges in multilingualism, context, and human-machine collaboration in Q&A and dialogue systems. We aim to revolutionize the service experience for consumers in Southeast Asia and globally.

By integrating state-of-the-art algorithmic technology, robust engineering foundations, thoughtful product design, and intelligent operations, our team has developed a rich, efficient, and high-performance Q&A technology system. This system significantly supports markets in Southeast Asia, including Singapore and Indonesia, as well as the South American market, including Brazil, effectively addressing the vast differences in customer service demands and controlling costs while improving customer satisfaction.

The rise of large language language models has opened up vast possibilities in the field of customer service. Natural dialogue and task-driven scenarios are crucial stages for showcasing the capabilities of LLMs. Here, you have the opportunity to build algorithmic systems based on large language models, redefining chatbots and agent assistance products, and bringing a novel user experience to a broad consumer base.
- Designing and developing algorithms related to AI assistants, including but not limited to LLM post-training/SFT/MoE, user preference alignment with RL(such as DPO/GPRO).
- Developing LLM-powered RecSys for intent recommendation, including retrieval, coarse&fine ranking, user sequential modelling & generative recommendation (GR) techniques.
- Designing and developing corresponding algorithm platforms and supporting tools.

**Requirements**:

- Bachelor's degree or higher in Computer Science or a related field.
- Proficiency in at least one programming language, such as Python, C++ & Go.
- Skilled in at least one mainstream deep learning framework, like PyTorch, TensorFlow.
- Passion for LLM-related technology and solving challenging real-world problems.
- Deep understanding of computer fundamentals, including data structures, algorithms, and machine learning.
- Familiarity with mainstream algorithmic models in large language models, natural language processing, recommendation, and multimodality (including principles and implementation).
- Prior research or internship experience in natural language Q&A or recommendation technology is preferred.
- Excellent English language skills in listening, speaking, reading, and writing.