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研究科学家实习生 - 2027年入职

雇主

TikTok

地点

California · San Jose · 美国

待遇

$面议

工作模式

线下

截止日期

1月8日

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岗位摘要

PhD research internship focused on advancing LLM/VLM capabilities with built-in trust and safety, co

岗位职责

Foundations & Intelligence Service, Trust & Safety is TikTok’s foundation-model team responsible for core development and research that push the boundaries of our LLM and VLM capabilities—with trustworthiness and safety built in from day one.
Our work enables product teams and customers to adopt advanced AI smoothly and responsibly, with safety woven into the model stack rather than bolted on.
We are looking for talented individuals to join us for an internship.
PhD internships at Our Company provide students with the opportunity to actively contribute to our products and research, as well as to the organization's future plans and emerging technologies.
Our dynamic internship experience blends hands-on learning, enriching community-building and professional development events, and collaboration with industry experts.
Applications will be reviewed on a rolling basis, so we encourage you to apply early.
Please clearly state your availability in your resume (Start date, End date).
Responsibilities:- Pretraining & Continued Pretraining (CPT): Explore and develop approaches that improve general capability and safety for LLMs and VLMs via pretraining/CPT.
- Evaluation & Measurement: Build advanced evaluation systems to study emerging LLM/VLM skills and safety behaviors, aligned with real downstream use.
- Post-Training & RL: Develop advanced reinforcement-learning strategies (e.g.,
RLHF/RLAIF/DPO variants), and investigate how to balance pretraining and post-training for better capability and safety alignment.
- Scaffolded Settings & Agents: Probe new failure modes and pitfalls in scaffolded environments (agents, workflows, tool use), and translate insights into robust mitigations.

申请条件

PhD student. Must clearly state availability in resume (start date, end date).

雇主简介

TikTok is a leading short-form video platform that develops core training and serving infrastructure for large-scale recommendation systems and AI infrastructure for foundation models and LLMs.

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数据来源:TikTok

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