Site Reliability Engineer Intern – Monetization Systems

Job Description

Software Engineer Intern (Global SRE) | TikTok

The Tone:
This is an internship at TikTok, likely located in Los Angeles, CA, offering students an opportunity to gain industry exposure and hands-on experience. TikTok builds the leading short-form mobile video platform, alongside large-scale, globally distributed, and fault-tolerant advertising systems. This role is crucial for ensuring the highest level of system availability and providing the best possible user experience within the monetization technology team.

The TL;DR
• Role: Internship
• Type: Full-time
• Location: Los Angeles, CA
• Pay: $45–$60 hourly
• Team: Monetization Technology Team
• Mission: Ensure high availability and optimal user experience for large-scale, globally distributed advertising systems.

What You’ll Actually Do
• System Lifecycle Management: Improve the entire lifecycle of Ads systems, covering design, deployment, operation, and refinement.
• Service Availability: Enhance the availability of services distributed across multiple data centers globally.
• Tool Development: Create software and tools to improve the reliability, scalability, and operability of services.
• Performance Monitoring: Measure and monitor critical service metrics such as availability, latency, and overall service health.
• Incident Management: Participate in sustainable incident response, postmortems, and on-call rotations across continents.

The Must-Haves
• Background: Currently pursuing an Undergraduate or Master’s degree in Computer Science, Computer Engineering, or a related technical discipline.
• Experience: Experience with problem-solving application issues, production operations, or automating routine tasks.
• Skills: Excellent programming, debugging, and optimization abilities in languages such as C, C++, Java, Python, Perl, or Go, coupled with familiarity with Unix/Linux operating systems, IP networking, and effective communication skills.
• Bonus: Experience in Site Reliability Engineering for Ads or recommendation systems, or in designing, analyzing, and troubleshooting large-scale distributed systems.