recommend/advertising systems / risk control systems / LLM
LIVE
Build prediction/uplift NN model
improve LIVE feature intelligence
Responsibilities
The strategy team's mission is to use model-driven and data-driven ways to promote core indicators on LIVE revenue and user engagement, which includes:
Build prediction/uplift NN model to improve LIVE feature intelligence;
Mine and interfere potential crowds to gain a higher ROI operation for both LIVE streamer and watcher;
Make detailed analysis on user data and system data to find out user experience optimiaztion zoom;
Other work like user growth strategy, cold-start strategy, etc.
Participate in the optimization of LIVE monetization business and serve the LIVE experience of billions of global users;
Adopt cutting-edge machine learning model to scientifically model massive user behaviour and consumption data, build high-performance/high-reliability architecture services, and bring users the ultimate experience in LIVE consumption;
Deeply participate in product/business discussions, fully analyze and understand user behaviour patterns, and provide optimization directions for the overall business.
Requirements
Currently pursuing a PhD in Computer Science or a related Engineer discipline.
Familiar with C/C++/ Python development, familiar with Linux multi-threaded /multi-process;
Familiar with commonly used machine learning and deep learning algorithms, including but not limited to boost machine, dnn, reinforcement learning, etc.;
Solid maths foundation, including probability statistics, numerical optimization, etc., sensitive to data, good at discovering, analyzing and solving problems from data;
Preferred
Familiar with at least one of Flink, Spark, Hive etc., with big data parallel processing experience;
Experience in large-scale recommend/advertising systems, risk control systems or LLM is preferred
Benefits
We are looking for talented individuals to join us for an internship.
PhD internships at Our Company provide students with the opportunity to actively contribute to our products and research, as well as to the organization's future plans and emerging technologies.
Our dynamic internship experience blends hands-on learning, enriching community-building and professional development events, and collaboration with industry experts.
Hiring process
Applications will be reviewed on a rolling basis, so we encourage you to apply early.
Please clearly state your availability in your resume (Start date, End date).
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