Ancestry
1001 - 5000 employees
Founded 1983
👥 B2C
🛍️ eCommerce
B2C • eCommerce
Ancestry is a consumer-focused family history company that helps people discover, preserve, and share their family stories through online genealogy tools, historical records, and consumer DNA testing. The company operates a subscription-based platform and eCommerce offerings (such as DNA kits), maintains a large consumer DNA database, and combines technology, data science, and content to power personal discovery and research. Ancestry emphasizes customer experience, diversity and inclusion, and employs global teams across product, engineering, marketing, and science-related roles.
Data Science – AI Document Understanding, Co-op
🔥 0 minutes ago
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Ancestry
1001 - 5000 employees
Founded 1983
👥 B2C
🛍️ eCommerce
B2C • eCommerce
Ancestry is a consumer-focused family history company that helps people discover, preserve, and share their family stories through online genealogy tools, historical records, and consumer DNA testing. The company operates a subscription-based platform and eCommerce offerings (such as DNA kits), maintains a large consumer DNA database, and combines technology, data science, and content to power personal discovery and research. Ancestry emphasizes customer experience, diversity and inclusion, and employs global teams across product, engineering, marketing, and science-related roles.
📋 Description
• 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). • 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using frameworks like LangChain, LangGraph, CrewAI, or AutoGen to automate complex multi-step reasoning tasks in historical document analysis.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 your 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. • Familiar 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.
🏖️ Benefits
• Flexible work arrangements • Professional development opportunities
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