- Design and develop ML algorithms and intelligent systems for large-scale e-commerce scenarios: recommendation, ranking, retrieval, forecasting, content understanding, pricing, governance, and conversational AI.
16 days
Be the first to hear about new jobs at Tiktok!
Tiktok Careers and Job Vacancies
- Large language Model Algorithm Development: Build domain-specific large language models (LLM/MLLM) for e-commerce, integrating domain knowledge to rapidly apply models to business scenarios.
16 days
- AI Search & AI Bot Team: Specializes in LLM application algorithm R&D for TikTok Search, covering core scenarios including AI Search Q&A cards and TikTok's official AI Assistant. We leverage LLM ChatBot, Agent, and RAG technologies to deliver accurate, real-time search responses for users, driving business growth through deep integration of technical innovation and business scenarios.
16 days
- Participate in building large-scale (billion level) E-commerce recommendation algorithms and systems, including commodity recommendations, live stream recommendations, short video recommendations etc.
16 days
- Responsible for the search system of TikTok and its affiliated products, and solving the architecture optimization problem of the search architecture system;
16 days
- Build global product catalog and content understanding systems, modeling products, videos, images, merchants, and brands with structured and semantic representations.
16 days
- Research on foundation models and frontier generative technologies: Explore the capability boundaries of large language models (LLMs) and multimodal large models (MLLMs), especially the evolution of foundation capabilities for agentic scenarios. Conduct in-depth research and propose innovative post-training paradigms, tackling challenges in complex reasoning such as CoT reasoning and long-horizon planning, tool use, reinforcement learning alignment such as innovative applications of PPO, GRPO, and other new RLHF algorithms for agent behavior alignment, reward model design, and AI safety. Build model capabilities for autonomous decision-making and reflection from the underlying architecture. Explore and break through the underlying architectures of frontier visual generation algorithms such as diffusion and flow matching, building a strong perception and environment simulation foundation for multimodal agents.
16 days
- Build and optimize infrastructure for large-scale model training and online inference.
16 days
- Recommendation Large Models: Address challenges such as gradient convergence and representation drift in ultra-long behavioral sequences, enabling the system to achieve true ""logical reasoning"" capabilities.
16 days
- Explore the integration of foundation models with ranking algorithms to improve personalized ranking accuracy and user experience.
16 days