About the role#
The E-commerce Global Supply Chain and Logistics team builds AI-native capabilities for our global operations. We focus on logistics agents, address intelligence, context engineering, and workflow automation. This internship is for candidates interested in applying LLMs, reinforcement learning, and retrieval systems to logistics problems at a global scale. You will contribute to our research and products while working with industry experts.
What you'll do#
- Support the development of large language models and agent systems for global e-commerce logistics.
- Build domain-specific LLM capabilities, including continued pre-training, SFT, preference optimization, and reinforcement learning (GRPO/PPO).
- Design reward or judge models, optimize inference costs, and work on scenarios like address correction, trajectory prediction, and root-cause analysis.
- Develop multimodal understanding for logistics, integrating text, numerical time series, product attributes, and documents to support decision systems.
- Create core agent capabilities such as task decomposition, RAG, knowledge retrieval, and tool use.
- Manage agent architecture, including runtime orchestration, memory management, model routing, and observability.
- Build evaluation frameworks, including benchmark sets, regression testing, and online feedback loops.
What you'll need#
- Currently pursuing a PhD in artificial intelligence, computer science, operations research, automation, statistics, mathematics, or a related field.
- Experience with LLMs, agents, RAG, tool use, post-training, or applied NLP systems.
- Strong Python programming skills and familiarity with at least one production language like Java, C++, Go, or TypeScript.
- Proficiency with frameworks such as PyTorch, TensorFlow, JAX, vLLM, Hugging Face, LangChain, or LlamaIndex.
- Research or project experience in coding agents, workflow orchestration, or automated evaluation systems.
- Experience with LLM post-training techniques like SFT, DPO, PPO, GRPO, RLHF, or RLAIF.
- Experience building benchmarks from real user data, including taxonomy design and error attribution.
- Background in e-commerce, logistics, knowledge graphs, or data platforms is a plus.
- A portfolio of published papers, open-source contributions, or hands-on projects in AI engineering or machine learning systems.
Location & details#
- Location: San Jose, California.
- Modality: On-site.
- Employment: Full-time internship.
- Compensation: $60 per hour.
- Status: Paid position.
- Hiring process: Applications are reviewed on a rolling basis.
About TikTok
TikTok operates as an entertainment provider. The company maintains a global presence with offices in cities including Los Angeles, Singapore, New York, London, and Tokyo. It employs over 92,000 people. The organization is privately held.
How to get in at TikTok
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