Site Reliability Engineer, AI Applications

TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and its offices include New York, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join Us
Creation is the core of TikTok's purpose. Our products are built to help imaginations thrive. This is doubly true of the teams that make our innovations possible. Together, we inspire creativity and enrich life - a mission we aim towards achieving every day. To us, every challenge, no matter how ambiguous, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always. At TikTok, we create together and grow together. That's how we drive impact-for ourselves, our company, and the users we serve. Join us.

Team Intro
The Speech team's mission is to empower content interaction and creation using speech & audio related technologies. The team focuses on cutting-edge R&D in areas like speech & audio, music processing, natural language understanding and multimodal deep learning. We are looking for top talents to work on these exciting technologies, integrate them into various products and ultimately bring joy to our global user base!

Responsibilities
We are seeking a talented and experienced Site Reliability Engineer (SRE) to join our dynamic team. This role focuses on the reliability, scalability, and performance of our AI applications. The ideal candidate will have a strong background in both software engineering and systems engineering, with a particular emphasis on maintaining and optimizing AI and machine learning infrastructure. The major responsibilities include:
- Monitoring and Incident Response: Develop and implement monitoring solutions to track the performance and reliability of AI systems. Respond to incidents, diagnose issues, and implement fixes to minimize downtime.
- Automation and Tooling: Automate repetitive tasks, streamline deployments, and create tools to improve the efficiency and reliability of AI operations.
- Performance Optimization: Analyze and optimize the performance of AI applications and the underlying infrastructure, including tuning algorithms and resource management.
- Capacity Planning: Forecast infrastructure needs and ensure that the AI applications have the necessary resources to handle future workloads.
- Security: Implement and maintain security best practices to protect data and applications, ensuring compliance with relevant regulations.
- Documentation: Create and maintain detailed documentation of infrastructure, processes, and procedures to ensure knowledge sharing and continuity.
- Continuous Improvement: Identify opportunities for process improvements and implement solutions to enhance the reliability and performance of AI systems.