TikTok is looking to optimize the app experience related to performance for its users, specifically focusing on live streaming and Real-Time Communication (RTC) scenarios.
Requirements
- In-depth understanding of the fundamental architecture and implementation of live streaming/RTC systems; candidates with optimization experience in live streaming/RTC projects are preferred.
- Proficient in C++/Python; candidates with deep expertise in machine learning, reinforcement learning, or causal inference technologies are preferred.
- Experience with learning-based model development is a big plus.
Responsibilities
- Responsible for optimizing multiple adaptive strategies in live streaming/RTC scenarios for client-side (push/pull streaming), including performance adaptation, network adaptation, playback control adaptation, etc.
- Responsible for optimizing multiple adaptive strategies in live streaming/RTC scenarios for server-side (transcoding), including dynamic transcoding, dynamic bitrate delivery strategies, dynamic traffic allocation strategies, etc.
- Responsible for mapping and analyzing multiple QoS/QoE metrics in live streaming/RTC scenarios, building QoE models for different user groups, and continuously optimizing personalized strategies for live streaming.
Other
- Successful candidates must be able to commit to an onboarding date by end of year 2026. Please state your availability and graduation date clearly in your resume.
- Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply.
- Strong sense of responsibility, curiosity, and excellent collaboration and communication skills, with the ability to accurately abstract problems and prioritize in complex technical scenarios.
- Excellent problem solving, data analysis, communication, and team work skills
