About the role#
The Recommendation Architecture team builds and optimizes the systems that power TikTok video recommendations. As a project intern, you will work on short-term projects to gain professional experience and develop practical skills in a real-world engineering environment. This is a full-time, paid internship.
What you'll do#
- Build large-scale recommendation systems for a global audience.
- Create efficient and reliable data pipelines for candidate generation, profile generation, training examples, and real-time online training.
- Coach AI to manage release processes and production operations, including online anomaly detection, diagnostics, and release safeguards.
What you'll need#
- Currently pursuing an undergraduate or master degree in Computer Science, Computer Engineering, or a related technical discipline.
- Programming experience in C, C++, Java, or Golang.
- Strong communication skills.
- A sense of ownership and drive.
- Experience with AI coding is a plus.
Location & details#
- Location: San Jose, California.
- Modality: On-site.
- Term: Rolling basis.
- Compensation: $45 per hour.
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.
