Senior Machine Learning Engineer / Machine Learning Expert

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 Data and Agent teams to design and implement robust RAG (hybrid search, ranking optimization) and search architectures, ensuring highly relevant document retrieval for complex scientific queries.
• Model Post-training: Utilize post-training skills to enhance LLMs' reasoning capabilities and understanding on Materials Science data extraction.

Qualifications

• Minimum Qualifications
• Bachelor's degree or higher in Computer Science, Artificial Intelligence, or a related quantitative field.
• Proficient in leveraging AI-enhanced development tools such as Claude Code, solid programming skills in Python with a focus on algorithmic implementation.
• 3+ years of hands-on experience in NLP/LLM/RAG, with a proven track record of deploying complex information extraction systems in production.
• Excellent communication skills with the ability to understand product requirement, solve data/RAG related challenges within a cross-functional team.


• Preferred Qualifications
• RAG & Data: Deep experience in high-quality data processing and building production-grade RAG systems (including vector databases, hybrid search, and re-ranking).
• Model Refinement: Proven ability to enhance extraction accuracy through post-training techniques, including NER, prompt engineering, and instruction fine-tuning.
• Domain Expertise: Familiarity with Physics, Chemistry, or Biology (e.g., understanding of molecular structures or material properties) is a significant plus.