Site Reliability Engineer

Job description:

Site Reliability Engineering (SRE) combines software and systems engineering with the art of machine learning to build and run large-scale, massively distributed, and fault-tolerant systems. You will have the opportunity to sharpen your expertise in coding, performance analysis, and large-scale system design while making a tangible impact on the future of TikTok's Infrastructure services and AML systems.

Responsibilities

• Design, build, and maintain highly available, scalable, and fault-tolerant systems. Collaborate with software engineering teams to ensure applications are designed with reliability and performance in mind. • Develop and maintain automation procedures to maximize system efficiency, minimize human intervention, and optimize routine tasks. • Monitor and analyze system performance to identify and address bottlenecks before they impact users. Ensure the infrastructure can handle rapid growth in web traffic and ML data processing. • Participate in 24/7 on-call rotations (including scheduled shifts and holidays). Practice sustainable on call response, conduct root-cause analysis, and lead blameless post-mortems to prevent recurrence. • Implement monitoring tools (SLIs/SLOs/SLAs) and set up automated alerting and metrics to track system health and performance. • Implement and maintain security best practices and ensure all systems meet regulatory requirements.

Job Requirements Minimum Qualifications:

• Education: Bachelor's or Master's degree in Computer Science, Information Technology, Computer Engineering, or a related field. • Experience: 3+ years of experience as a Site Reliability Engineer, Systems Engineer, or Software Engineer. • Coding: Proficient in at least one high-level programming language (e.g., Python, Go, C++, or Java) and shell scripting. Strong understanding of data structures and algorithms. • Systems: Strong understanding of Linux operating systems and open-source technologies and a solid understanding of network architecture. • Databases: Competent knowledge of relational database systems and database modeling.

Preferred Qualifications: • Experience with containers and container orchestration platforms such as Docker and Kubernetes. • Proficiency in or exposure to machine learning frameworks such as TensorFlow, PyTorch, MXNet, or PaddlePaddle. • Hands-on experience with monitoring tools and methodologies (e.g., Prometheus, Grafana). • Soft Skills: Strategic thinking, exceptional communication, and the ability to collaborate effectively with cross-functional teams in a fast-paced environment.