Agentic AI Discovery Co-Op - Part-Time Hybrid Research

Ancestry; Lehi (UT); Hybrid; USD 2,755,000 - 6,199,000; Part time

Job summary

Ancestry seeks an Applied AI Science Co-Op to advance agentic personalization and personalized discovery experiences. Join a team building multi-agent AI systems, memory-driven personalization, and tool-use frameworks for scalable, real-world results.

We value candidates pursuing a PhD with strong ML research background, Python/SQL/PyTorch proficiency, and familiarity with agentic AI and retrieval systems. This is a part-time, work-study opportunity aligned with graduate studies.

Qualifications

• Pursuing an advanced degree (PhD strongly preferred) in CS/AI or related field.
• Experience with applied ML research and published work in top venues is a plus.
• Proficient in Python, SQL, and PyTorch with ML system experience.

Responsibilities

• Research and develop agentic personalization systems using customer data and AI.
• Explore memory, profiling, and embedding-based approaches for personalization.
• Build hybrid agentic recommender systems with LLM orchestration.

Skills

Python

SQL

PyTorch

ML Systems

Education

PhD candidate

Tools

LangGraph

DSPy

AutoGen

CrewAI

vLLM

Qdrant

FAISS

Job description

Ancestry seeks an Applied AI Science Co-Op to advance agentic personalization and personalized discovery experiences. Join a team building multi-agent AI systems, memory-driven personalization, and tool-use frameworks for scalable, real-world results.

We value candidates pursuing a PhD with strong ML research background, Python/SQL/PyTorch proficiency, and familiarity with agentic AI and retrieval systems. This is a part-time, work-study opportunity aligned with graduate studies.