LLM & AI Agent Engineer - Multilingual Search

rednote; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

rednote is building the next generation of global community products with a focus on multilingual understanding and AI-native search and recommendation. The Global Search & Recommendation Algorithm Team drives core expansion efforts including translation, multilingual foundation models, and AI-powered search and recommendations.

The role covers post-training of multilingual and multimodal models, deployment of translation technologies, and the development of AI agents to enhance both

Qualifications

• Bachelor’s degree or higher in CS/AI/EE/Automation/SE/Math or related field.
• Strong fundamentals in machine learning; publications in leading conferences are a plus.
• Research or internship experience in LLM, search/recommendation systems, NLP, or multilingual tech preferred.
• Strong programming skills in Java, C++, or Python; solid data structures and algorithms.
• Good English communication skills and ability to work in cross-cultural environments.
• Ownership mindset, analytical thinking, and the ability to think abstractly.

Responsibilities

• Multilingual and Multimodal LLM post-training: drive post-training of multilingual and multimodal foundation models and deployment of multilingual translation tech.
• Develop AI agents for recommendation algorithms to improve performance via memory, retrieval, and agent-based paradigms.
• Develop AI agents for search algorithms, exploring AI-powered search, generative retrieval, and LLM-based relevance.

Skills

Machine Learning Fundamentals

LLM Research Experience

NLP & Multilingual Tech

English Communication

Education

Bachelor's degree or higher in Computer Science, Artificial Intelligence, Electronic Information Engineering, Automation, Software Engineering, Mathematics, or related field

Tools

Java

C++

Python

Job description

rednote is building the next generation of global community products with a focus on multilingual understanding and AI-native search and recommendation. The Global Search & Recommendation Algorithm Team drives core expansion efforts including translation, multilingual foundation models, and AI-powered search and recommendations.

The role covers post-training of multilingual and multimodal models, deployment of translation technologies, and the development of AI agents to enhance both