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Recommendation Large Model Algorithm Engineer-TikTok Algorithm
2 weeks ago
The TikTok R&D team is dedicated to building and maintaining industry-leading products that drive the success of TikTok's global business. By joining us, you'll work on core scenarios such as user growth, social features, live streaming, e-commerce consumer side, content creation, and content consumption, helping our products scale rapidly across global markets. You'll also face deep technical challenges in areas like service architecture and infrastructure engineering, ensuring our systems operate with high quality, efficiency, and security. Meanwhile, our team also provides comprehensive technical solutions across diverse business needs, continuously optimizing product metrics and improving user experience.
Here, you'll collaborate with leading experts in exploring cutting-edge technologies and pushing the boundaries of what's possible. Every line of your code will serve hundreds of millions of users. Our team is professional and goal-oriented, with an egalitarian and easy-going collaborative environment.
Research Project Introduction:
With the advancement of hardware computing and the continuous breakthroughs of large models in CV/NLP/multimodal learning and even AGI fields, the large computing driven in recommendation scenarios are increasingly capable of capturing user preferences in a more comprehensive and nuanced way. This enables a deeper understanding of user needs and the discovery of latent interests, ultimately leading to enhanced user experiences.
As a critical component of short video recommendation systems, the ranking module is responsible for fine-grained matching between users and content, selecting the videos users are most likely to be engaged with. In this context, the key research focus is how to best leverage large computing to maximize the model's memory, generalization, and reasoning capabilities.
Qualifications
1. Got doctor degree, preferably in Artificial Intelligence, Computer Science, Mathematics, or other related fields.
2. Strong programming skills with a good foundation in data structures and fundamental algorithms. Proficient in various algorithmic and engineering frameworks.
3. Publications in top-tier international conferences or journals (including but not limited to ACL, EMNLP, NeurIPS, ICML, ICLR, CVPR etc) is a plus.
4. Strong foundation in machine learning, with in-depth understanding and research experience in deep learning, reinforcement learning, NLP, and multimodal learning.
5. Outstanding communication and collaboration skills, with the ability to work with the team to explore new technologies and drive innovation
