Senior Lead AI Engineer
# Senior Lead AI Engineer **Zalo** · Thành phố Hồ Chí Minh · `On-site` 🕒 **Статус:** *Опубликовано: вчера* · *Источник: Indeed* --- ### About the Role Hồ Chí Minh Full-time We are seeking a proactive and talented Senior Lead NLP / AI Engineer to join our AdTech team. In this role, you will be instrumental in transforming raw advertising text into actionable intelligence - extracting keywords, intent, and semantic meanings, and generating high-dimensional vector embeddings to drive our CTR/CVR prediction models and ad-triggering engines. Beyond core ad data processing, you will also play a key role in driving internal efficiency by building AI Agents and automated workflows to streamline repetitive engineering processes within the team. What you will do Ad Text Processing & Feature Extraction: Build and maintain scalable pipelines to process unstructured ad content (titles, descriptions, keywords) and extract key signals such as topics, intent, and semantic meanings; Vector Embedding Generation: Convert textual data into dense vector embeddings to serve as high-quality feature inputs for downstream Machine Learning models; Model Integration & Ad Targeting: Feed extracted features and embeddings into CTR (Click-Through Rate) and CVR (Conversion Rate) prediction models, as well as real-time Ad Triggering & Semantic Matching engines; Internal Process Automation via AI Agents: Research, design, and deploy internal AI Agents and automated workflows to automate repetitive operational tasks and data processing routines within the team. What you will need Domain & Technical Experience: Proven experience in NLP and Feature Engineering, ideally within AdTech, Search, E-commerce, or Recommendation Systems; NLP & Embedding Expertise: Strong hands-on experience with text vectorization techniques (e.g., Sentence-Transformers, Hugging Face models, BGE, OpenAI embeddings) and keyword/entity extraction; Ad-Model Understanding: Clear understanding of how textual features and vector representations impact CTR/CVR predictive models and vector-based ad retrieval/matching algorithms; AI Agent & Automation Skills: Practical experience or strong familiarity with AI Agent frameworks and orchestration tools (e.g., LangChain, LlamaIndex, CrewAI, AutoGen, n8n, or Dify); Tech Stack: Proficiency in Python, standard ML/NLP libraries (PyTorch, TensorFlow, SpaCy, Hugging Face), and experience working with Vector Databases (e.g., Qdrant, Pinecone, Milvus, FAISS). Nice To Have Experience optimizing GPU infrastructure, model quantization, and distillation; Experience building MCP servers/tool libraries; Experience with audit trail and compliance systems for AI in large enterprise environments.
Наблюдалась 2026-09-15, впервые 2026-09-15, источник — Indeed.