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TikTok

Machine Learning Engineer (AI Search), TikTok Search

Aug 26, 2025• Singapore

About us

TikTok is the leading destination for short-form mobile video and our mission is to inspire creativity and bring joy.

★ 4.5 out of 5 · 6 reviews

  • Size: 10,000+ employees
  • Industry: Technology: Consumer Internet
View company profile ›

Why you should apply for a job to TikTok:

  • 4.5/5 in overall job satisfaction
  • 4.5/5 in supportive management
  • 100% say women are treated fairly and equally to men
  • 100% would recommend this company to other women
  • 100% say the CEO supports gender diversity

Ratings are based on anonymous reviews by Fairygodboss members. See all reviews ›

Responsibilities

Our Search Team focuses on LLM application algorithms for TikTok Search, with core scenarios including AI Search and TikTok AI Bot. We build search question-answer cards via LLM-powered generation and develop TikTok's official AI assistant, leveraging LLM ChatBot, Agent, and RAG technologies to deliver accurate, real-time responses. By closely integrating technical innovation with business scenarios, we bridge users with information and services, driving TikTok's business growth.

Responsibilities:
- Build AI Search Agents with planning, memory, and tool-use capabilities. Apply reinforcement learning, knowledge representation, and automated decision-making to solve complex problems end-to-end.
- Enhance LLM-based query understanding: process multi-turn conversations, conduct semantic analysis on queries and documents, and ensure accurate, objective search results via LLM reasoning.
- Optimize RAG and LLM pipelines: improve retrieval and ranking algorithms, train and optimize LLMs for answer generation (e.g., fine-tuning, inference optimization), and enhance the relevance and structured presentation of search results.
- Translate research (e.g., Agent/LLM innovations) into production, collaborating with cross-functional teams to drive product upgrades.

Qualifications

Minimum Qualifications
- Proficient in C++/Python; strong command of algorithms and data structures (e.g., retrieval, graph algorithms).
- Basic understanding of LLM fundamentals (e.g., prompt engineering, fine-tuning workflows).
- Strong problem-solving skills with a track record of delivering technical projects.

Preferred Qualifications
- Hands-on experience with LLM/Agent technologies: RAG optimization, RLHF/SFT for LLMs, or Agent framework development (e.g., planning/memory modules).
- Excellent communication and collaboration skills, with a track record of exploring new technologies and driving technical advancements with teams.

Responsibilities

Responsibilities

Our Search Team focuses on LLM application algorithms for TikTok Search, with core scenarios including AI Search and TikTok AI Bot. We build search question-answer cards via LLM-powered generation and develop TikTok's official AI assistant, leveraging LLM ChatBot, Agent, and RAG technologies to deliver accurate, real-time responses. By closely integrating technical innovation with business scenarios, we bridge users with information and services, driving TikTok's business growth.

Responsibilities:
- Build AI Search Agents with planning, memory, and tool-use capabilities. Apply reinforcement learning, knowledge representation, and automated decision-making to solve complex problems end-to-end.
- Enhance LLM-based query understanding: process multi-turn conversations, conduct semantic analysis on queries and documents, and ensure accurate, objective search results via LLM reasoning.
- Optimize RAG and LLM pipelines: improve retrieval and ranking algorithms, train and optimize LLMs for answer generation (e.g., fine-tuning, inference optimization), and enhance the relevance and structured presentation of search results.
- Translate research (e.g., Agent/LLM innovations) into production, collaborating with cross-functional teams to drive product upgrades.

Qualifications

Qualifications

Minimum Qualifications
- Proficient in C++/Python; strong command of algorithms and data structures (e.g., retrieval, graph algorithms).
- Basic understanding of LLM fundamentals (e.g., prompt engineering, fine-tuning workflows).
- Strong problem-solving skills with a track record of delivering technical projects.

Preferred Qualifications
- Hands-on experience with LLM/Agent technologies: RAG optimization, RLHF/SFT for LLMs, or Agent framework development (e.g., planning/memory modules).
- Excellent communication and collaboration skills, with a track record of exploring new technologies and driving technical advancements with teams.

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Additional Information

  • Posted: Aug 26, 2025
Apply on company site
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