Graduate Research Co-op - AI & Representation Learning

About the role

Ancestry is a human-centered company dedicated to connecting people with their pasts. We offer a vast collection of over 65 billion records, support over 3.5 million subscribers, and have a DNA network of over 27 million people. Our commitment to flexibility allows employees to work in offices, from home, or a hybrid of both, depending on location and role requirements.

Responsibilities

• Support the development of representation learning models to integrate massive-scale hierarchical data with diverse record sets.
• Evaluate and benchmark diverse machine learning models to resolve data conflicts and improve the accuracy of relationship discovery at scale.
• Assist in building scalable ML prototypes that analyze billions of data points to provide automated insights and personalization.
• Develop efficient data pipelines to process and vectorize massive-scale datasets for downstream research and modeling tasks.
• Collaborate closely with senior researchers to document findings and prepare technical reports on model performance and scalability.

Requirements

• Currently enrolled in a Graduate program (Ph.D. preferred, or MS) in Computer Science, Data Science, or a related quantitative field.
• Solid understanding of Representation Learning, Embedding models, or Large-scale Data Modeling.
• Proficient in Python and modern ML frameworks such as PyTorch or TensorFlow; familiarity with Vector Databases or Large Language Models (LLMs) is a plus.
• Strong analytical skills with the ability to extract meaningful insights from massive-scale, complex datasets.
• A collaborative spirit and a desire to see research translated into real-world applications.

Qualifications

• Passionate about dedicating your work to enriching people’s lives.
• Experience in genomic data analysis and enthusiasm in human populations and/or family history.

Skills

• Representation Learning
• Embedding models
• Large-scale Data Modeling
• Python
• PyTorch or TensorFlow
• Vector Databases
• Large Language Models (LLMs)

Benefits

Equal Opportunity Employer. Reasonable accommodations for qualified individuals with disabilities. Background check required. San Francisco Fair Chance Ordinance applies to candidates living in San Francisco, CA.