Machine Learning Engineer (AI Search ) - TikTok Search

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
- 5 years of experience in Machine Learning, preferably in a fast-paced, high-growth environment.
- 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).