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# Software Engineer, AI Infrastructure - USDS

- **Company:** Tiktok Inc.
- **Location:** San Jose, CA, United States
- **Salary:** $122,574.0 - $259,200.0
- **Contract:** Internship / Graduate position
- **Skills:** Artificial Intelligence, Computer Programming, Data Centers, Linux, DevOps, Distributed Systems, Fault Tolerance, Github, Python (Programming Language), Machine Learning, Networking Basics, Software Engineering, AI Infrastructure, Gitlab-ci, Kubernetes, Information Technology, Performance Monitor, Search Engines, Docker, Jenkins
- **Published:** June 5, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=7a3aa9de9d956cc8

## About the Role

Do you have experience in Tooling?, Do you have a Bachelor's degree?, Minimum Qualifications: - Bachelor's degree in Computer Science or a related technical field, with 1+ years of professional experience in software development or infrastructure. - Solid understanding of Linux systems and networking fundamentals. - Proficiency in programming with Python or Go, with a focus on writing clean and efficient automation tools. - Experience working with Docker and basic CI/CD pipelines (e.g., Jenkins, GitLab CI, or GitHub Actions). - Foundational knowledge of distributed systems and a strong interest in troubleshooting complex technical issues. - Effective communication skills and a proactive approach to solving engineering bottlenecks. - Experience with agentic frameworks and tools development. Preferred Qualifications: - Prior experience or internships focused on SRE, DevOps, or internal platform engineering. - Familiarity with container orchestration tools like Kubernetes. - Basic understanding of the machine learning lifecycle or model
inference workflows.

## Description

About the Team The USDS JV AI Infra SRE team works with engineering and product teams to build and run large-scale, globally distributed, observable, fault-tolerant systems for TikTok state-of-the-Art Recommendation and Search engines. SREs on this team will deliver on production ownership and be responsible for observability and automation across complex, large-scale service mesh architectures. Responsibilities: - Assist in the deployment, operation, and optimization of Recommendation and Search systems throughout their entire lifecycle. - Develop and maintain internal software and automation scripts to eliminate manual tasks and improve overall R&D velocity. - Support the availability of large-scale services deployed across global data centers through proactive monitoring and maintenance. - Track and report on cloud resource utilization to help the team meet efficiency goals and maintain cluster SLAs. - Configure and manage monitoring stacks to track service latency, health metrics,
and system performance.


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