Research Scientist Intern — AI Safety & LLM/VLM

TikTok

San Jose (CA)

Hybrid

USD 68,000 - 97,000

Full time

14 days+
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Benefits offered by this job

Health insurance
Housing allowance
10 paid holidays per year

Job summary

TikTok is offering a PhD internship with Foundations & Intelligence Service, focusing on core AI development and safety for LLMs and VLMs. You will contribute to research that enables safe, scalable deployment and collaboration with product teams.

The program blends hands-on research, community building and professional development, with rolling applications and an emphasis on availability, safety and responsible AI practices. Start date and duration to be specified in resume.

Qualifications

  • Currently pursuing a PhD in Computer Science or a related technical field.
  • Research experience in LLMs, AI Safety, Computer Vision or Multimodality.
  • Keep up with AI-safety developments and terminology.
  • Proficient with at least one deep learning framework (PyTorch or TensorFlow).
  • Strong analytical, communication and collaboration skills.

Responsibilities

  • Pretraining & Continued Pretraining: develop approaches to improve general capability and safety for LLMs/VLMs.
  • Evaluation & Measurement: build evaluation systems for LLM/VLM safety behaviors.
  • Post-Training & RL: explore RLHF/RLAIF/DPO variants for alignment.
  • Scaffolded Settings & Agents: investigate failures and mitigations in scaffolded environments.

Skills

LLMs
AI Safety
Computer Vision
Multimodality

Education

PhD candidate in Computer Science

Tools

PyTorch
TensorFlow

Job description

TikTok is offering a PhD internship with Foundations & Intelligence Service, focusing on core AI development and safety for LLMs and VLMs. You will contribute to research that enables safe, scalable deployment and collaboration with product teams.

The program blends hands-on research, community building and professional development, with rolling applications and an emphasis on availability, safety and responsible AI practices. Start date and duration to be specified in resume.

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