About TravelokaTraveloka is Southeast Asia’s leading all-in-one travel platform connecting millions globally with trusted, world-class experiences. With over 140 million app downloads and more than 40 million monthly active users, Traveloka stands as one of the most popular travel apps in the region.

Job Description

Job ID: MJ000208

We are building a brand-new, high-impact AI and algorithm team within our core business units. As a Senior Algorithm Engineer, you will lead the design and implementation of next-generation generative AI capabilities, focusing on core areas such as intelligent customer service chatbots, translation agents, and travel-related conversational assistants.

This is a highly autonomous and impactful role. You will not only participate in the definition and development of AI products from scratch, but also directly drive their large-scale application in real-world business scenarios. Your work will directly impact the service experience, problem-solving efficiency, conversion rates, and operating costs for millions of users.

Key Responsibilities

• Responsible for the design, development, and continuous optimization of intelligent customer service chatbot and AI agent systems, covering key scenarios such as pre-sales consultation, itinerary inquiries, order support, after-sales service, and multilingual translation.
• Build agent architectures for complex business processes, including task planning, tool invocation, memory management, retrieval enhancement, workflow orchestration, multi-turn dialogue management, and anomaly recovery.
• Design and optimize natural language understanding and generation capabilities for travel and customer service scenarios, including user intent recognition, context modeling, knowledge-based question answering, response generation, and multilingual interactive experiences.
• Drive the deployment of large-scale models in vertical businesses, exploring methods such as Prompt Engineering, RAG, SFT, and preference optimization to continuously improve answer quality, task completion rate, and user satisfaction.
• Establish an evaluation system for intelligent customer service and agents, including offline assessment, automated evaluation, manual quality inspection, online A/B testing, and continuous iteration mechanisms.
• Collaborate closely with product, engineering, data, and operations teams to promote deep integration of AI capabilities with business systems, ensuring that solutions offer high availability, low latency, scalability, and cost-effective production-grade performance.
• Monitor key performance indicators (KPIs) of agents in real-world scenarios, including problem resolution rate, human agent referral rate, first-response latency, average processing time, satisfaction, cost, and stability, and continuously optimize these metrics.

Job Requirements:

• 5+ years of experience in algorithm engineering, machine learning, NLP, or related fields, with successful experience deploying AI or machine learning systems in large-scale production environments.
• Possesses strong practical experience in generative AI/LLM applications, and is familiar with the core technologies and implementation challenges of intelligent customer service, question-answering systems, dialogue systems, or agent-type products.
• Proficient in Python and familiar with mainstream machine learning/deep learning frameworks such as PyTorch, TensorFlow, and Scikit-Learn.
• Familiar with the key technology stack for large-scale model applications, including prompt design, RAG, vector retrieval, model fine-tuning, inference optimization, tool usage, and multi-turn dialogue management.
• Possesses solid engineering capabilities, capable of independently driving the entire closed loop from data analysis, modeling experiments, performance evaluation to online deployment and iterative optimization.
• Possesses excellent business understanding and cross-team collaboration skills, capable of transforming complex AI capabilities into stable, measurable, and sustainably optimizable business results.
• Bachelor's degree or above, with preference given to candidates with a background in Computer Science, Artificial Intelligence, Data Science, Statistics, Mathematics, or related quantitative fields.

Bonus points:

• Experience with customer service chatbots, enterprise knowledge assistants, translation agents, task-oriented dialogue systems, or AI copilots.
• Experience with multilingual models, cross-language retrieval, machine translation, or internationalization products, especially in complex travel or service scenarios.
• Familiarity with LangGraph, LangChain, OpenAI/Anthropic/open-source large model ecosystems, or experience in building agent workflows.
• Experience in model evaluation, AI security, visual governance, policy control, human-machine collaboration, and the design of mechanisms for transferring data to human intervention.
• Familiarity with vector databases, retrieval systems, Elasticsearch, Milvus, Redis, and other related infrastructure.
• Experience in OTA, travel, e-commerce, or high-concurrency online service scenarios is preferred.
• Experience in search, recommendation, or ranking is a plus, but not mandatory.