AI Systems and ML Scientist

AI Systems and ML Scientist

Requirements

• 3+ years of experience developing AI and Generative AI solutions to drive automation and business process efficiencies.
• Must-have experiences include working on projects involving large language models (LLMs) and techniques such as Retrieval-Augmented Generation (RAG), Dense Passage Retrieval (DPR), Knowledge Graphs, Fine-tuning and Prompt engineering.
• Proficient in using classification, clustering, and dimensionality reduction.
• Experience in implementing and managing CI/CD pipelines to automate the deployment and testing of data and AI solutions.
• Experience in working with manufacturing datasets, cloud computing and cloud data services (e.g. Snowflake, EC2, EMR, RDS, Redshift) and vector databases (e.g. Pinecone, Chroma, Weaviate, etc.) for handling high-dimensional and unstructured data.
• Proficient in designing and developing web-based user interface (UIs) and real-time dashboards using Streamlit and Power BI and other web development frameworks such as React for better insights and improved decision making.
• Strong skills in Python are essential. Knowledge of other languages like R, Java, or C++ can be beneficial.
• Data analysis and modelling using open-source software libraries, SIMCA, Dataiku and JMP.
• Database design/management tools: MS SQL Server, MySQL, and PostgreSQL.
• Data visualization and web development frameworks: Power BI, Streamlit, React and similar frameworks.
• Big Data/cloud platforms: AWS, Snowflake, Azure.
• Other relevant software such as MS office, software for project management and agile activity tracking.
• Formal training and certification or self-learned demonstratable skills as a ML/AI data scientist.

Responsibilities

• Develop AI systems and Agentic Systems using Generative AI and programmatic techniques (40%).
• Develop standard and modular data engineering, visualization, AI solutions for rapid modernization of process monitoring and troubleshooting capabilities (30%).
• Partner with manufacturing operations, Digital, Smart Factory and other global functions to enable Sanofi’s new and legacy facilities with contextualized process data to facilitate timely data-driven decision making (20%).
• Upskill and train MSAT Global Data Science network in terms of ML and AI techniques (10%).

Preferred Qualifications

• PhD – preferred.