About the role#
The TikTok Video team builds the systems behind the For You Feed. We work at the intersection of machine learning and large-scale systems. Our team designs and operates the end-to-end pipeline, from offline training data orchestration to real-time online inference, to support our recommendation experience.
What you'll do#
- Build globalized large-scale recommendation systems.
- Develop efficient and reliable data pipelines for candidate generation, ranking, profile generation, training examples, and real-time online training.
- Coach AI to handle release processes and production operations, including online anomaly detection, diagnosis, and release safeguards.
What you'll need#
- Currently pursuing a Bachelor's or Master's degree in Computer Science or a related technical field.
- Experience programming in C, C++, Java, or Golang.
- Effective communication skills with a strong sense of ownership.
- Experience with AI coding is a plus.
Location & details#
- Location: San Jose, California.
- Term: Summer 2027.
- Modality: On-site.
- Employment: Full-time internship.
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.
