AI Search Algorithm Engineer

PERSOL SINGAPORE PTE. LTD.; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

PERSOL SINGAPORE PTE. LTD. is seeking a senior AI/Search engineer to lead both traditional and generative AI search pipelines, architecting scalable retrieval, ranking, and LLM-integrated components for global search scenarios and production deployment.

You will drive optimization across query understanding and multi-stage retrieval while improving recall and relevance. Collaborate with engineering, product, and research teams to deliver robust AI products, emphasizing RAG retrieval, memory

Qualifications

• Master's or PhD degree in Computer Science, Artificial Intelligence, Data Science, or other related fields.
• Solid foundation in machine learning and deep learning, with understanding of information retrieval, search and recommendation systems, and NLP/LLM.
• Proficiency in Python, C++, or Java, and familiarity with PyTorch and TensorFlow. Experience in large-scale distributed training is a plus.
• Research or industrial experience in search-related areas including semantic query understanding, multi-stage retrieval and ranking, and LLM data augmentation.
• Strong analytical and problem-solving skills to identify search quality issues from large-scale logs and optimize performance.
• Excellent teamwork and communication, collaborating with engineering, product, research, and cross-functional teams.
• 2–3+ years of R&D in search algorithms is preferred and valuable for this role.

Responsibilities

• Lead the engineering development and production deployment of traditional search systems with continuous optimization across query understanding, multi-stage retrieval, and personalized ranking.
• Lead the engineering development and production deployment of the generative AI search pipeline using LLM and RAG retrieval, including task planning and tool invocation capabilities.
• Collaborate with cross-functional teams to drive successful project implementation and deliver impactful AI products.

Skills

Python

C++

Java

PyTorch

TensorFlow

Distributed training

Search systems

Analytical skills

Teamwork

R&D in search

Education

Master's or PhD in CS/AI/DS or related field

Tools

PyTorch

TensorFlow

Job description

Lead the engineering development and production deployment of the full traditional search systems, driving continuous optimization across query understanding, multi-stage retrieval, relevance modeling, and personalized ranking. Integrate LLM technologies with traditional search architectures to enhance semantic understanding for global search scenarios, improving search recall, relevance, and user engagement metrics.

Lead the engineering development and production deployment of the full generative AI search pipeline. Leverage deep expertise in LLM and RAG retrieval to architect and integrate task planning, tool orchestration, memory management, and result self verification capabilities. Optimize hybrid indexing and knowledge segmentation strategies to improve AI-generated search quality, relevance, and click through performance.

Qualifications

• Master's or PhD degree in Computer Science, Artificial Intelligence, Data Science, or other related fields.
• Solid foundation in machine learning and deep learning, with solid understanding of fundamental theories and methods in information retrieval, search and recommendation systems, and natural language processing/large language model etc.
• Proficiency in at least one programming language among Python, C++, or Java, and familiarity with mainstream deep learning frameworks such as PyTorch and TensorFlow. Experience in large-scale distributed training is an added advantage.
• In-depth research or industrial implementation experience in search-related areas, including but not limited to semantic query understanding, multi-stage retrieval and ranking, relevance filtering, multi-objective ranking, LLM data augmentation, RAG retrieval augmentation, AI Agent task planning and tool invocation.
• Strong analytical and problem-solving skills, with the ability to efficiently identify search quality issues from large-scale search logs, develop multi-objective optimization strategies, and balance key performance metrics including retrieval recall, search relevance, user click-through rate, and model instruction-following capability.
• Excellent teamwork and communication skills, with the ability to collaborate effectively with engineering, product, research, and cross-functional teams to drive successful project implementation.
• Candidates with 2~3+ years of R&D experience in search algorithms (content/news/document/application search, etc.) is preferred. Strong business awareness, ownership, and a passion for developing impactful AI products will be considered valuable advantages.

We regret to inform that only shortlisted candidates will be notified.