Machine Learning Engineer Graduate (Conversational AI) - 2027 Start

About the job

Team Introduction

We build the next-generation unified Agent system for TikTok's global e-Commerce customer service — running in 30+ languages across one of the largest e-Commerce surfaces on the internet.

Our north star is a self-evolving Agent: post-training, harness, memory / context engineering, tools, and evaluation form one closed loop, and every served conversation becomes the next iteration's training / eval / retrieval / skill-induction signal. This loop is already running in production — cases are mined, root-caused, turned into constrained candidates, replayed against frozen regression sets, and shipped behind guardrails.

Two things make this team different from most "LLM application" work:

• We build the agent runtime itself — Codex / Claude-Code-class — not prompts on top of a vendor API.
• Evaluation and experimentation are first-class systems, not an afterthought. A self-improving loop optimizes whatever signal you give it, so the hardest and most valuable engineering here is making the judgment trustworthy — not just making the model change.

By combining generative recommendation, large recommendation models, multimodal representation learning, and cross-domain value modeling, the team works on some of the most important algorithmic problems in live commerce. Our goal is to improve user experience, optimize ecosystem efficiency, and drive sustainable business growth for TikTok Shop across global markets.