AI Search Algorithm Engineer

Beijing Foreign Enterprise Management Consultants Co.,Ltd.; Singapore; On-site; SGD 120,000 - 250,000; Full time

Job summary

Huawei is seeking passionate and talented individuals to join our team as AI Agent Development Engineer. You will lead the engineering development and production deployment of full traditional search systems, driving optimization across query understanding, multi-stage retrieval, relevance modeling, and personalized ranking.

You will also lead the generative AI search pipeline, leveraging LLM and RAG retrieval to architect and integrate task planning, tool orchestration, memory management, and

Qualifications

• Master's or PhD in Computer Science, Artificial Intelligence, Data Science, or related fields.
• Solid foundation in machine learning and deep learning with understanding of IR, search + recommender systems, NLP/LLMs.
• Proficiency in Python, C++, or Java; familiarity with PyTorch and TensorFlow; experience with large-scale distributed training preferred.
• Experience in search-related areas: semantic query understanding, multi-stage retrieval and ranking, RAG, LLM data augmentation, tool invocation.

Responsibilities

• Lead engineering development and deployment of traditional search systems with optimization across query understanding, retrieval, relevance scoring and ranking.
• Lead AI search pipeline development leveraging LLMs, RAG, task planning, tool orchestration, memory management, and verification capabilities.

Skills

Programming languages

Analytical thinking

Teamwork

Communication skills

R&D experience

Education

Master's or PhD in CS/AI/DS

Tools

PyTorch

TensorFlow

Job description

On behalf of Huawei, a world-renowned information and communication technology company, we are seeking passionate and talented individuals to join our team as AI Agent Development Engineer.

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.

Skills / 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 preferred.
• 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.