About the role#
The Monetization GenAI team builds generative technology for text, images, video, and landing pages. You will work on research projects that improve creative efficiency for advertisers and creators. This internship is for PhD students starting in 2026.
What you'll do#
- Research and advance technology in large language models and multimodality generative model architectures.
- Implement and evaluate new machine learning algorithms.
- Work with applied machine learning and infrastructure teams to put generative models into ad production.
What you'll need#
- You are currently pursuing a PhD in computer science, machine learning, or a related field.
- You have hands-on experience developing multimodality foundation models.
- You have a strong record of publications in top conferences or journals like NeurIPS, ICML, ICLR, or CVPR.
- Previous research or internship experience in an AI organization is a plus.
Location & details#
- This role is based in San Jose, California.
- This is a full-time, on-site, paid internship.
- 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
Landing an internship at TikTok requires speed because early applicants often get seen before the pile grows. Intern Insider sends an instant alert the moment a role matching your target is published anywhere, so you can apply among the first. This gives you a better chance of your resume being reviewed while the team is still actively filling the position. You should aim to be one of the first people to submit your materials. Reaching out to the right person can also improve your chances of getting a response. Intern Insider surfaces the recruiters behind the company roles so you can contact them directly to ask about the role or a referral. This direct approach often works better than waiting for a response from a general application queue.
