The role
From TikTok's own posting.
TikTok Ads Core ML Team aims at creating automatic delivery products for the next generation and developing advertising as a business, instead of just a monetization tool to consolidate the delivery funnel framework allowing multiple teams to iterate parallel.
We're looking for innovative Staff Research Engineers to join our Core ML Ranking team. Ads Core Ranking team specifically focuses on maximizing delivery system efficiency and revenue growth through state-of-the-art models and frameworks. Our research topics include but not limited to: Generative Retrieval and Large Recommendation Model, LLM-based Ranking Application, and Optimization of System Resource Allocation with ROI target.
As part of our team, you will be responsible for:
- Spearhead the development of a global advanced advertising delivery system by integrating cutting-edge technologies and research, including ML/DL, Reinforcement Learning, LLM, and scaling laws, within complex monetization scenarios.
- Optimize efficiency across the entire advertising funnel, covering Recall & Rough-sort, Fine-sort (CTR/CVR), format/creative personalization, and system resource allocation.
- Lead strategic initiatives and drive key projects by leveraging deep business acumen in monetization, ranking, search, and recommendation, ensuring precise technical decision-making.
- Establish and refine system frameworks and standards, continuously enhancing efficiency to meet diverse vertical business needs.
- Collaborate with product and business teams across global markets to maximize impact.
All of our team effort is to continuously pursue and establish a world-leading ranking model & framework that always benefits our collaborators, users and customers to get better returns.
Minimum Qualifications:
- MS or above degree in Computer Science, Statistics, Operation Research, Applied Mathematics, Physics or similar quantitative fields, with related experience in any of the following domains: search, ranking or recommendation.
- Hands-on experience in one or more of the following areas: machine learning, deep learning, statistical models and applied mathematical methods.
- Solid programming skills, proficient in C/C++ and Python. Familiar with basic data structure and algorithms. Familiar with Linux development environment.
- Familiarity with online experimentation and analytics.
- Familiarity with big data systems including Hadoop and Spark.
- Familiar with architecture and implementation of at least one mainstream machine learning programming framework (TensorFlow/Pytorch/MXNet).
- Curiosity towards new technologies and entrepreneurship.
Preferred Qualifications:
- Experience in reinforcement learning, transfer learning, and counter-factual optimization is a plus.
- Understanding of the business value of online advertising.
- Paper publications in NLP/CV/recommender system domain areas (such as, paper listing, workshop, oral on RecSys/KDD/ICML/NeurIPs/CVPR, etc. ).
- Experience in LLM is a plus.