Job Description
Job Overview We are looking for a visionary Machine Learning Engineer to build the next generation of knowledge extraction engines for Materials Science. In this role, you will go beyond simple text processing to tackle the most challenging aspects of patents and academic papers: complex table reconstruction, experimental workflow synthesis, chemical property mapping, and multimodal chart analysis. You will leverage NER, RAG, post-training to transform massive unstructured scientific literature into high-value, structured R&D databases.
Responsibilities
- Data Extraction Pipelines: Develop end-to-end solutions integrating OCR, Layout Analysis, and Semantic Parsing to precisely capture chemical formulas, experimental parameters, and performance metrics from complex documents. Resolve cross-modal data alignment between body text and complex scientific visuals (e.g., tables, chemical structures, and charts).
- RAG Development: Partner with Da...
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