AI Ads Product Manager-based Beijing

We are building the next-generation AI advertising monetization platform, providing intelligent ad recommendation capabilities for applications such as AI Chat, AI Search, and AI Agents. By understanding user prompts, contextual semantics, and interaction intent, and combining large language models (LLMs) with advertising algorithms, we aim to achieve precise ad matching while improving advertiser ROI and developer revenue. Responsibilities As an AI/Algorithm Product Manager, you will be responsible for planning and delivering AI advertising recommendation products, including: 1. Lead the product planning of AI advertising recommendation solutions and design ad-matching capabilities based on Prompts, Conversation Context, and User Intent. 2. Collaborate with algorithm, LLM, and advertising engineering teams to continuously optimize advertising strategies and improve ad relevance and conversion performance. 3. Conduct in-depth research into AI capabilities such as Prompt Understanding, Intent Understanding, and Semantic Matching, and apply them to advertising recommendation scenarios. 4. Establish an advertising performance evaluation framework and continuously optimize key metrics such as CTR, CVR, eCPM, ROI, and advertising revenue. 5. Design AI advertising product capabilities, including Prompt Processing, Keyword Extraction, Context Understanding, Embedding Retrieval, RAG, and other related capabilities. 6. Drive collaboration across the advertising platform, recommendation system, LLM services, and data platform to design and implement end-to-end product solutions. 7. Track the latest developments in Generative AI, Agents, Recommendation Systems, and Ads Ranking, and continuously innovate based on business needs. Basic Qualifications 1. Bachelor's degree or above; majors in Computer Science, Artificial Intelligence, Data Science, Mathematics, or related fields are preferred. 2. 3+ years of internet product management experience, including at least 2 years of experience in AI products, algorithm products, or recommendation systems. 3. Strong data analysis skills, with the ability to drive product iteration through experimentation and data. Professional Qualifications Candidates with experience in one or more of the following areas will be preferred: 1. Experience with advertising platforms (Ad Platforms), ad recommendation, ad ranking, or advertising monetization products. 2. Experience with recommendation systems, search, feeds, content recommendation, or personalized recommendation products. 3. Familiarity with the fundamentals of Large Language Models (LLMs), including Prompt Engineering, Embeddings, RAG, Function Calling, and Agents. 4. Understanding of the core recommendation algorithm pipeline, including Recall, Ranking, Re-ranking, and multi-objective optimization. 5. Familiarity with applying NLP, semantic understanding, intent recognition, and vector retrieval technologies to real-world products. 6. Ability to work with algorithm engineers to define model optimization strategies and understand model evaluation metrics such as Precision, Recall, NDCG, and AUC. 7. Familiarity with A/B Testing, online experimentation platforms, and data analysis methodologies, with the ability to continuously optimize products. Preferred Qualifications 1. Experience with AI products such as AI Chat, AI Search, AI Agents, or Copilots. 2. Experience with advertising systems such as DSP, SSP, RTB, recommendation advertising, or native advertising. 3. Familiarity with leading LLM ecosystems, including OpenAI, Gemini, Claude, DeepSeek, and Llama. 4. Project experience in ad retrieval, ad ranking, Semantic Ads, Contextual Advertising, or Conversational Ads. 5. A solid technical background and the ability to read algorithm documentation and communicate effectively with R&D teams. What We’re Looking For 1. Passionate about AI products and closely follows the latest developments in Generative AI. 2. Excellent logical thinking, product abstraction, and cross-functional collaboration skills. 3. Able to identify problems through data and continuously drive product optimization. 4. Strong interest in combining advertising monetization, recommendation systems, and AI technologies, with a willingness to explore the next generation of AI advertising products and experiences.