Responsibilities
Team Introduction: TikTok is an international short video platform covering 150 countries and regions. We hope to discover real and interesting moments through TikTok and make life better. TikTok has offices around the world, with global headquarters in Los Angeles and Singapore, and offices in New York, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul and Tokyo. The TikTok R&D team aims to realize the R&D work of TikTok business and build and maintain industry-leading products. Join us and you will be exposed to core business scenarios including user growth, social networking, live broadcasting, e-commerce C-end, content creation, content consumption, etc., supporting the rapid development of products on the global track you will also be exposed to technical challenges in service architecture, basic technology and other directions, ensuring that the business continues to serve users with high quality, high efficiency, and security at the same time, it can also provide comprehensive technical solutions for different business scenarios, optimize various product indicators and user experience. Here, there are big cows leading the team to continuously explore the frontier and break through the imagination space. Here, every line of your code will serve hundreds of millions of users. Here, the team is professional and pure, and the cooperative atmosphere is equal and relaxed. Currently, multiple job opportunities are open in Beijing, Shanghai, Hangzhou, Guangzhou and Shenzhen. 1. Responsible for TikTok's content ecosystem business recommendation algorithm, work closely with product, operation and other teams, deeply understand the development of TikTok's recommendation business, and jointly formulate long-term and short-term business goals 2. Deeply participate in machine learning technology research, form a complete system of working methods or experiences while solving specific problems, and continuously improve user experience 3. Research directions include but are not limited to: deep learning, graph neural networks, multi-task learning, Learning to rank, model compression and acceleration, multimodal technology, etc., good at combining actual business problems to carry out technical exploration and research 4. Organize and promote intra-group and cross-departmental cooperation projects to help the team progress and newcomers grow.
Qualifications
1. Familiar with LLM/MLLM, with practical large model tuning and application experience is a plus 2. Familiar with optimization ideas such as Prompt/Sft/Continuous Pretrain/Fine-tuning/Distillation, and actively pay attention to cutting-edge AI related technologies and papers 3. Good understanding and application of computer language/vision and other related fields, including but not limited to: dialogue system, video understanding, multi-modal understanding, etc. 4. Familiar with training methods such as self-supervision, unsupervised, contrastive learning and The theoretical basis is relatively familiar.
