Postdoc, Applied AI for Autonomous Document Understanding

Ancestry; Lehi (UT); Hybrid; USD 80,000 - 110,000; Full time

Job summary

Ancestry is seeking a Postdoctoral Research Fellow to join the AI Applied Science Content team. You will lead research at the intersection of industry-scale data and academic rigor, designing AI-native agentic systems to unlock insights from billions of historical records.

Work focuses on autonomous multi-agent workflows, transforming unstructured records into structured knowledge. We value publications, Python proficiency, and cloud expertise, with flexible location options.

Qualifications

• Ph.D. in Computer Science or related quantitative field.
• Strong publications in NLP, CV, or AI disciplines preferred.
• Experience with embeddings, vector databases, and transformer models.
• Proficiency in Python and cloud platforms; ability to communicate complex ideas.

Responsibilities

• Lead research at the intersection of industry-scale data and academic rigor.
• Design agentic multi-agent workflows for document understanding tasks.
• Transform unstructured historical records into structured, searchable knowledge.
• Evaluate multi-modal models and NLP/CV components; improve performance and reliability.

Skills

Python

NLP

CV

LLMs

Cloud platforms

Communication

Education

Ph.D. in Computer Science or related field

Tools

LangChain

LangGraph

CrewAI

AutoGen

Google Cloud

SageMaker

Job description

Ancestry is seeking a Postdoctoral Research Fellow to join the AI Applied Science Content team. You will lead research at the intersection of industry-scale data and academic rigor, designing AI-native agentic systems to unlock insights from billions of historical records.

Work focuses on autonomous multi-agent workflows, transforming unstructured records into structured knowledge. We value publications, Python proficiency, and cloud expertise, with flexible location options.