Senior/Lead Data Scientist (Applied AI Research)

Job description

Why LINE MAN Wongnai LINE MAN Wongnai is one of Thailand's fastest-growing technology companies, operating three core business groups: On-demand Services under the LINE MAN brand, the leader in food delivery, mart delivery, messenger, transportation, and telepharmacy; Merchant Digital Solutions under the Wongnai brand, the leading provider of POS and digital solutions for merchant management, beauty, and wellness clinics; and Pay & Financial Services under the LINE Pay brand, an integrated online and offline payment platform. As a data and AI-driven company, our mission is to Digitalize Everyday Life Services, guided by our core values: Innovate Faster, Go Deeper, and Respect Everyone. Together, we power a digital ecosystem that serves 10 million users, 520,000 active online and offline merchants, and over 290,000 active riders and drivers nationwide. We are currently seeking a Data Scientist (Applied AI Research) to join our team. In this pivotal role, you will bridge the gap between emerging AI techniques and scalable production solutions. You will explore cutting-edge open-source models, experiment with fine-tuning techniques, and build harnesses while maintaining a grounded focus on business impact. This role requires an inquisitive research mindset paired with strong AI and software engineering fundamentals. Join us, and you'll work alongside talented, driven people who take real ownership from day one. Here, your work won't just move a project forward, it'll shape how millions of people live every day. What you’ll Do: Collaborate closely with engineering teams to design and deploy end-to-end LLM applications that drive measurable business impact. Implement scalable LLMOps workflows to streamline model training, deployment, monitoring, and ongoing optimization in production. Evaluate, test, and benchmark frontier and open-source LLMs to identify high-value applications across our product ecosystem. Adapt and fine-tune pre-trained models using domain-specific datasets and modern optimization techniques. Establish robust evaluation frameworks, testing harnesses, and monitoring infrastructure to ensure AI models optimize for accuracy, latency, safety, and cost efficiency. Stay at the forefront of AI research, continuously evaluating emerging tools, architectures, and methodologies to enhance engineering practices. What you’ll Need: Bachelor’s, Master’s, or Ph.D. in Computer Science, Data Analytics, Statistics, or a related quantitative field. 2–5 years of experience in data science, machine learning, or applied research. Solid foundation in statistics, probability, machine learning algorithms, and large language models (LLMs). Hands-on experience with some modern AI tooling and frameworks (e.g., vLLM, LangChain, or similar execution engines). Strong problem-solving skills, strong sense of ownership, and a passion for translating experimental research into production-grade systems. Excellent communication skills with both technical and non-technical stakeholders, with a proven ability to build and foster collaborative relationships. Ability to thrive in a dynamic, fast-paced environment and apply disciplined risk control to deliver high standards under constraints. Fluency in both English and Thai. It’d be Great if you have: (if any) Demonstrated experience deploying and optimizing LLM serving architectures for high-concurrency, low-latency production applications. Extensive hands-on experience training, post-training, fine-tuning (e.g., LoRA, QLoRA), and aligning (e.g., RLHF, DPO) large language or multimodal models. Familiarity with modern Retrieval-Augmented Generation (RAG) frameworks, vector databases (e.g., Pinecone, Milvus, Qdrant), and advanced retrieval techniques. Experience building agentic workflows, function calling pipelines, or multi-agent orchestration systems. Proven track record of publishing research papers at top-tier AI/ML conferences or journals.