Data Science Researcher (LLM Applications)

💡 How You Will Drive Innovation

In this role, you will champion innovation at the intersection of Generative AI and industrial analytics. From engineering optimization (e.g., ASU engineering) to operational efficiency (e.g., ASU, SMR, Electronics Specialty Gases), you will bridge business strategy with frontier technology. Specifically, you will:

• Partner with business units to understand core challenges, translate requirements into functional design specifications, and engineer impactful solutions. Identify, evaluate, and collaborate with key industrial or academic partners as needed.
• Lead and participate in the design, development, and deployment of AI solutions based on Large Language Models (LLMs) to address key challenges in industrial, R&D, and healthcare domains.
• Fine-tune and optimize leading open-source LLMs (e.g., Llama, Qwen, DeepSeek) for domain-specific scenarios, including technical document comprehension, process parameter optimization, safety report analysis, and scientific knowledge discovery.
• Apply advanced Retrieval-Augmented Generation (RAG) techniques, integrating internal knowledge bases (patents, engineering manuals, technical reports) with external data to build highly accurate intelligent Q&A, content generation, and knowledge management systems.
• Develop and validate functional prototypes to rigorously test and evaluate solution performance.
• Build production-ready business tools based on validated prototypes, lead smooth handoffs to operational entities, and provide ongoing support for industrial deployment.
• Empower team members by sharing methodologies and best practices, ensuring long-term solution sustainability across Air Liquide.
• Drive knowledge transfer within Air Liquide and publish findings in internal R&D reports, top conferences, and peer-reviewed journals.
• Collaborate closely with IT and cross-functional teams to curate, clean, visualize, and extract insights from complex industrial data.
• Stay ahead of the curve in NLP, LLM, and Generative AI advancements (e.g., AI Agents, Multimodal AI), proactively evaluating and integrating new technologies to continuously elevate team capabilities.

🎯 What We Are Looking For:

• M.S. or Ph.D. in Computer Science, Artificial Intelligence, Statistics, Mathematics, Data Science, Engineering, or a related quantitative field. Proven independent and interdisciplinary research experience is strongly preferred.
• Solid, practical experience in LLM fine-tuning with a deep understanding of its principles.
• In-depth understanding of RAG architecture with hands-on experience in building and deploying complete RAG pipelines. Proficiency with mainstream frameworks (e.g., LangChain, LlamaIndex).
• Strong statistical foundation (e.g., probability distributions, regression models) is required. Familiarity with advanced statistical methods (clustering, dimensionality reduction like PCA/PLS, Bayesian networks, time-series modelling) and core machine learning algorithms (decision trees, random forests, SVM) is a big plus.
• Strong programming proficiency in Python and/or R. Working knowledge of C++, Java, or JavaScript is an advantage.
• Excellent written and verbal communication skills. Comfortable working in English daily within a diverse, global, and multi-disciplinary team environment. Conversational French is a plus.