- Remote, United States
- Remote
- Internship · Entry
This fellowship is designed for a researcher at the intersection of industry-scale data and academic rigor. The role involves leading research at the forefront of Document Understanding, designing and implementing AI-Native agentic systems to unlock insights from billions of historical and genealogical records.
Responsibilities
- Innovate with State-of-the-Art AI for tasks such as OCR/HTR, transcription, Named Entity Recognition (NER), Relation Extraction (RE), Coreference Resolution, Summarization, and Knowledge Graphs.
- Design and implement multi-agent workflows using frameworks like LangChain, LangGraph, CrewAI, AutoGen, AgentCore, Strands, Google ADK, A2A.
- Evaluate the performance of multi-modal AI & LLMs such as GPT, Gemini, Claude, Llama, and Qwen for zero-shot and few-shot scenarios.
- Apply NLP techniques including NER, Relation Extraction, Coreference Resolution, Entity Resolution, Knowledge Graphs, spaCy, NLTK, BERT.
- Apply Computer Vision (CV) expertise using models like YOLO, Nougat, DONUT, OpenCV for layout analysis.
Requirements
- Ph.D. in Computer Science
- Data Science
- Statistics
- Linguistics
- Engineering