Job Description

Responsibilities

• Responsible for analysing and understanding of the massive structured and unstructured data by NLP tasks, such as data processing, NER, relationship extraction, NOR etc.
• Own and improve our information-extraction pipeline, from model to production
• Solve document-level extraction at scale — design how we handle long documents where entities, properties, and their relationships span across sections
• Independently drive algorithm optimization, develop and fine-tune models to meet business requirements.
• Build hybrid systems combining NER, rule-based methods, and LLMs, applying each where it genuinely wins
• Define evaluation methodology / annotation strategy / quality metrics with domain experts
• Process and extract from large-scale corpora reliably and efficiently

Qualifications

• Master or Bachelor degree in Computer Science or related field.
• 4+ years of hands-on NLP/ML engineering in production, owning model or pipeline quality
• Proven experience with long-document / document-level information extraction and normalization
• Solid engineering fundamentals from working at scale
• Strong in NER, entity methodology; across rule-based, statistical, and LLM-based methods
• Experience in vibe coding and solid coding skills.