Data Science - AI Document Understanding, Co-op

About the role

Ancestry is a human-centered company dedicated to connecting people 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 a location flexible work approach allows employees to choose between working from home, in the office, or a hybrid model.

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, working with diverse genealogical and historical collections.
• Analyze and optimize multi-modal models: Evaluate the performance of multi-modal models in zero-shot and few-shot learning scenarios for comprehensive document understanding.
• Architect agentic systems: Design and implement multi-agent workflows using frameworks like LangChain, LangGraph, CrewAI, or AutoGen to automate complex multi-step reasoning tasks in historical document analysis.
• Evaluation & observability: Establish "LLM-as-a-Judge" frameworks and use tools like Arize Phoenix, DeepEval, or RAGAS to monitor for hallucination, drift, and bias.
• Collaborate on cloud deployment: Partner closely with ML Ops and Data Science Engineers to seamlessly deploy datasets, models, and pipelines in cloud environments.
• Communicate insights effectively: Clearly and confidently present findings, deliverables, and proposed solutions to technical and non-technical audiences, including teams, stakeholders, and executives.

Requirements

• Currently pursuing an advanced degree (Master's or PhD preferred) in Computer Science, Data Science, Statistics, Mathematics, Linguistics, Engineering or related quantitative field with a strong data focus.
• Specialization in AI & LLMs including familiarity with foundational models such as GPT, Gemini, Qwen, Llama, Claude, etc.
• Experience with inference optimization, vLLM, LoRA, QLoRA, quantization, etc.
• Familiarity with embeddings, vector databases, transformer models, with software development experience.
• Strong proficiency in Python and relevant tools and libraries, including transformer models, multi-modal models, and general NLP (e.g., Hugging Face Transformers, agentic frameworks and workflows, LangChain, LangGraph, CrewAI, AgentCore).
• 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 is a plus.

Qualifications

This is a part-time, work-study-based opportunity designed for active master's and PhD students continuing their education in the fall.

Skills

• Advanced degree (Master's or PhD preferred)
• Specialization in AI & LLMs
• Experience with AI and LLMs
• Software development experience
• Familiarity with cloud platforms and related AI/ML services

Benefits

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.

Pay

Details TBD

Schedule

Part-time, work-study-based opportunity