Postdoctoral Fellow, Applied AI Document Understanding

About the role

Ancestry is a human-centered company dedicated to connecting everyone with their past. We are the global leader in family history, offering over 65 billion records, 3.5 million subscribers, and a DNA network of over 27 million people. Our commitment to location flexibility allows employees to work from home, in an office, or a hybrid model, subject to location restrictions and role requirements.

Responsibilities

• Innovate with state-of-the-art AI: Implement cutting-edge AI solutions for key Document Understanding tasks such as OCR/HTR, transcription, Named Entity Recognition (NER), Relation Extraction (RE), Coreference Resolution, Summarization, and Knowledge Graphs using diverse genealogical and historical collections.
• Architect agentic systems: Design and implement multi-agent workflows using frameworks like LangChain, LangGraph, CrewAI, AutoGen, AgentCore, Strands, Google ADK, A2A, etc., to automate complex multi-step reasoning tasks in historical document analysis and information extraction.
• Analyze and optimize multi-modal models: Evaluate the performance of multi-modal AI & LLMs such as GPT, Gemini, Claude, Llama, and Qwen for zero-shot and few-shot scenarios in comprehensive document understanding.
• Natural Language Processing (NLP): Specialize in NER, Relation Extraction, Coreference Resolution, Entity Resolution, Knowledge Graphs (Neo4j), spaCy, NLTK, BERT.
• Computer Vision (CV): Apply expertise using models like YOLO, Nougat, DONUT, OpenCV, etc., to perform layout analysis, identify text blocks, headers, tables, and deeply nested lists.
• Evaluation & observability: Establish ensemble models and "LLM-as-a-Judge" frameworks, and use tools like Arize Phoenix, DeepEval, or RAGAS to monitor or hallucination, drift, and bias.
• Development productivity: Familiarity with "AI coding" workflows and usage of AI coding assistants such as Amazon Q, Cursor, Claude Code, and Kiro to accelerate development cycles.
• Collaborate on cloud deployment: Partner with ML Ops to deploy datasets, models, and pipelines in cloud environments like AWS (S3, SageMaker, Bedrock, ECS, EKS) and GCP (Vertex AI, Gemini API).

Requirements

Ph.D. (recent graduate or near completion) in Computer Science, Data Science, Statistics, Linguistics, Engineering, or a related quantitative field with a strong research focus. A strong record of academic publications in NLP, CV, or Agentic AI is preferred. Specialization in AI & LLMs, including familiarity with foundational models such as GPT, Gemini, Qwen, Llama, Claude, etc. Research in inference efficiency and optimization, potentially using vLLM, LoRA, QLoRA, and quantization approaches. Familiarity with embeddings, vector databases, and transformer models, with software development experience. Strong proficiency in Python and relevant tools and libraries, including transformer models and multi-modal models. Familiarity with cloud platforms and related AI/ML services such as Google CloudPlatform, GCP, Gemini API, Vertex AI, AWS EC2, S3, SageMaker, Model Registry, and Bedrock are a plus. Ability to clearly present complex technical solutions to both technical and non-technical stakeholders.

Qualifications

Ability to clearly present complex technical solutions to both technical and non-technical stakeholders.

Skills

Ph.D. (recent graduate or near completion) in Computer Science, Data Science, Statistics, Linguistics, Engineering, or a related quantitative field with a strong research focus. A strong record of academic publications in NLP, CV, or Agentic AI is preferred. Specialization in AI & LLMs, including familiarity with foundational models such as GPT, Gemini, Qwen, Llama, Claude, etc. Research in inference efficiency and optimization, potentially using vLLM, LoRA, QLoRA, and quantization approaches. Familiarity with embeddings, vector databases, and transformer models, with software development experience. Strong proficiency in Python and relevant tools and libraries, including transformer models and multi-modal models. Familiarity with cloud platforms and related AI/ML services such as Google CloudPlatform, GCP, Gemini API, Vertex AI, AWS EC2, S3, SageMaker, Model Registry, and Bedrock are a plus. Ability to clearly present complex technical solutions to both technical and non-technical stakeholders.

Benefits

Location flexibility: Work from home, in an office, or a hybrid model, subject to location restrictions and role requirements.

Pay

Competitive salary based on experience and qualifications.

Schedule

Flexible work schedule to accommodate personal and professional needs.

Additional Information

Ancestry is an Equal Opportunity Employer that makes employment decisions without regard to race, color, religious creed, national origin, ancestry, sex, pregnancy, sexual orientation, gender, gender identity, gender expression, age, mental or physical disability, medical condition, military or veteran status, citizenship, marital status, genetic information, or any other characteristic protected by applicable law. In addition, Ancestry will provide reasonable accommodations for qualified individuals with disabilities. All job offers are contingent on a background check screen that complies with applicable law. For candidates who live in San Francisco, CA, pursuant to the San Francisco Fair Chance Ordinance, Ancestry will consider for employment qualified applicants with arrest and conviction records. Ancestry is not accepting unsolicited assistance from search firms for this employment opportunity. All resumes submitted by search firms to any employee at Ancestry via-email, the Internet or in any form and/or method without a valid written search agreement in place for this position will be deemed the sole property of Ancestry. No fee will be paid in the event the candidate is hired by Ancestry as a result of the referral or through other means.