SWE Intern: Build Scalable, Low-Latency Serving

TikTok; San Jose (CA); On-site; USD 51,000 - 73,000; Full time

Benefits offered by this job

Health insurance on day one

Paid holidays (10 days)

Housing allowance

Job summary

TikTok is seeking a Campus Intern for the Recommendation System Infrastructure team to help build and evolve large-scale online serving and data infrastructure for global recommendations. You will work on high-performance C++ systems, collaborate across teams, and participate in hands-on projects, development workshops, and social events while gaining real-world experience in infrastructure engineering.

Interns may apply to up to two positions; rolling reviews prioritize availability dates, with

Qualifications

• Pursuing Bachelor's degree in Computer Science or related technical discipline.
• Proficient in at least one systems programming language (C++, C, Go, or Java).
• Experience building scalable backend systems, distributed systems, infrastructure systems, or high-performance online services.
• Solid understanding of data structures, operating systems, networking, and distributed system fundamentals.
• Experience with performance analysis, system debugging, reliability improvement, or large-scale service optimization.
• Strong ownership, problem-solving ability, and communication skills.
• Ability to work effectively with cross-functional teams, including infrastructure teams, recommendation algorithm teams, and product/business-facing engineering teams.

Responsibilities

• Design, build, and optimize high-performance online serving systems for large-scale global recommendation systems, improving business ROI, system efficiency, and serving quality.
• Improve the efficiency, reliability, scalability, and cross-regional consistency of recommendation system infrastructure.
• Identify and resolve system performance bottlenecks across CPU, memory, bandwidth, GPU compute efficiency, serving latency, throughput, and resource allocation efficiency.
• Drive cost optimization for large-scale recommendation serving, including business-impact-based cost efficiency, compute resource utilization, and infrastructure-level or strategy-level performance improvements.
• Build reliable and efficient workflows and pipelines for automation on candidate generation, profile generation, feature processing, training data generation, and online development.

Skills

Systems programming

Distributed systems

C++ / C / Go / Java

Performance analysis

Ownership & communication

Team collaboration

Education

Bachelor's degree in CS or related field

Master's degree candidate

Tools

Flink

Spark

Kafka

Job description

TikTok is seeking a Campus Intern for the Recommendation System Infrastructure team to help build and evolve large-scale online serving and data infrastructure for global recommendations. You will work on high-performance C++ systems, collaborate across teams, and participate in hands-on projects, development workshops, and social events while gaining real-world experience in infrastructure engineering.

Interns may apply to up to two positions; rolling reviews prioritize availability dates, with