AI Agent Algorithm Engineer

Shopee • Commerce • Master's Degree • Python • 5 days ago

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Location

In office (Singapore)

Seniority

Junior · 2+ years exp

First seen by Alion on Sep 24, 2026.

Overview

Company

Impact

Profile match

Shopee

Shopee is a multinational technology company and e-commerce marketplace platform operating as a subsidiary of Sea Limited. The company provides a hybrid B2C and C2C digital marketplace offering retail products, integrated digital payments and financial services via ShopeePay/SeaMoney, and end-to-end logistics and fulfillment solutions through SPX Express. Headquartered in Singapore, the platform serves millions of consumers and merchant partners across Southeast Asia, Taiwan, and Latin America.

shopee.com • HQ: Singapore • Commerce • 1001-5000 employees • Est. 2015

Tech stack of Shopee

Build core Agent logic, including but not limited to task planning and orchestration, tool calling, multi-turn dialogue management, memory, RAG, context engineering, and multi-agent collaboration.
Lead Continuous Pre-training and Post-training for vertical domains and business scenarios, including building high-quality datasets and data pipelines, designing RL reward models, improving instruction following and reasoning capabilities, task completion, role-playing, anthropomorphic and personalized dialogue, proactive/reactive immersive multimodal conversation experiences, and enhancing the model's IQ and EQ.
Build long-term and short-term memory architectures, addressing issues such as forgetting and attention dispersion in long contexts, and improving immersion and consistency in long-term user interactions.
Build multimodal RAG systems, including development and optimization of key modules such as recall, ranking, long-text processing, and multi-document synthesis.
Develop the Agent's tool layer, integrating external APIs and MCP such as search, code interpreters, browsers, sandboxes, and third-party services.
Design and tune prompts and context management, with tailored optimization for different product requirements.
Design scientifically rigorous quantitative evaluation systems and plans aligned with product requirements; continuously monitor product metrics and provide guidance for Agent and model optimization.
Explore innovative AI applications.

Master's degree or above in Artificial Intelligence, Computer Science, Mathematics, or a related field.
At least 2 years of full-time industry experience building and deploying production multi-agent LLM systems (task planning, orchestration, tool calling).
Hands-on experience fine-tuning LLMs via SFT and DPO, combined with hands-on experience building and optimizing RAG/retrieval systems (recall, ranking, embedding fine-tuning).
Good programming skills; proficient in Python
Good problem solving analysis and resolution skills; sustained interest and curiosity in frontier AI technologies and applications; strong self-drive; able to collaborate closely with teams to drive a full closed loop from research to deployment.
Good development experience with Agent frameworks such as LangGraph, Google Agent Development Kit, OWL, or AutoGen.

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