Job description

About Ancestry: When you join Ancestry, you join a human-centered company where every person’s story is important. Ancestry®, the global leader in family history, connects everyone with their past so they can discover, preserve, and share their unique family stories. With our unparalleled collection of more than 65 billion records, over 3.5 million subscribers, and over 27 million people in our growing DNA network, customers can discover their family story and gain a new level of understanding about their lives. Over the past 40 years, we’ve built trusted relationships with millions of people who have chosen us as the platform for discovering, preserving, and sharing the most important information about themselves and their families. We are committed to our location flexible work approach, allowing you to choose to work in the nearest office, from your home, or a hybrid of both (subject to location restrictions and roles that are required to be in the office- see the full list of eligible US locations HERE ). We will continue to hire and promote beyond the boundaries of our office locations, to enable broadened possibilities for employee diversity. Together, we work every day to foster a work environment that's inclusive as well as diverse, and where our people can be themselves. Every idea and perspective is valued so that our products and services reflect the global and diverse clients we serve. Ancestry encourages applications from minorities, women, the disabled, protected veterans and all other qualified applicants. Passionate about dedicating your work to enriching people’s lives? Join the curious. Ancestry is seeking an exceptional and highly motivated Postdoctoral Research Fellow to join our AI Applied Science Content team. This fellowship is designed for a researcher at the intersection of industry-scale data and academic rigor. In this role, you will lead research at the forefront of Document Understanding, designing and implementing AI-Native agentic systems to unlock insights from billions of historical and genealogical records. Your work will focus on advancing the state of the art in autonomous multi-agent workflows and on transforming unstructured historical records into structured, searchable knowledge that connects customers to their family history. What you will do: • 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 working with diverse genealogical and historical collections spanning newspapers, city directories, family history books, and vital records (i.e., birth, marriage, & death records). • 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): 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, identifying 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). Who You Are: • 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. • Familiar 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 Cloud • Platform, 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 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.

Requirements

Must-haves

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): 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, identifying 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).
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.
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.
Familiar 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 Cloud
Ability to clearly present complex technical solutions to both technical and non-technical stakeholders

Nice-to-haves

A strong record of academic publications in NLP, CV, or Agentic AI is preferred.
Platform, GCP, Gemini API, Vertex AI, AWS EC2, S3, SageMaker, Model Registry, and Bedrock are a plus.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aillmmlawsgcpapipython

Platform: careers-browser
Effort: medium

Benefits

Benefits detected in the listing.

Vision