RRemoteville
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Lead Applied Scientist

Skills
Artificial IntelligenceInformation RetrievalLarge Language ModelsMachine LearningNatural Language ProcessingRetrieval-Augmented GenerationSmall Language Models
Role

What the job involves

The main requirements, responsibilities and hiring steps.

Requirements

  • PhD in Computer Science AI NLP or related field or Master's with equivalent experience
  • Hands-on experience building document understanding information extraction or knowledge graph systems using deep learning LLMs and NLP
  • Ability to translate complex document understanding problems into innovative AI applications that balance accuracy and efficiency
  • Technical leadership mentoring and influence without formal authority in an applied research setting
  • Strong programming skills in Python and experience with PyTorch Hugging Face Transformers or DeepSpeed
  • Publications at venues such as ACL EMNLP ICLR NeurIPS SIGIR or KDD
  • Deep understanding of document understanding fundamentals including layout analysis semantic chunking hierarchical classification and imbalanced multi-label classification
  • Expertise in knowledge extraction and knowledge graph construction including entity recognition linking relation extraction and citation parsing
  • Expertise in LLM-based information extraction few-shot and multi-task learning post-training and knowledge distillation
  • Understanding of synthetic data generation techniques for NLP including query-answer generation with verification and data augmentation
  • Understanding of efficiency optimization including model compression and SLM-based solutions
  • Experience designing annotation workflows labeled datasets and evaluation frameworks for document understanding tasks

Nice to have

  • Strategic thinker
  • Research driven
  • Collaborative leader
  • Mentoring mindset
  • Domain curiosity

Day to day

  • Lead the design build test and deployment of end-to-end AI solutions for complex legal document understanding tasks.
  • Develop semantic chunking document enrichment and knowledge graph construction systems that support search and research across legal tax and accounting content.
  • Partner with engineering product and research stakeholders to deliver scalable reliable AI capabilities and mentor team members across multiple product lines.