Graduate Research Co-op - AI & Representation Learning
About The Position
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. 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. 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. We are looking for candidates with strong experience in genomic data analysis and enthusiasm in human populations and/or family history. Through regular mentorship from our scientists, you will gain valuable research experience for the next step in your career. You will have the opportunity to apply cutting edge computational and statistical approaches to the largest database of human genome and pedigree data in the world. You will develop methods to help millions of people understand their ancestry, their family, and themselves. Help us make an impact in this exciting field! Join the DNA Science team as a Co-op and conduct innovative research on the world’s largest genomic and pedigree database to further our knowledge on human populations and family history. This is a part-time, work-study focused position for 6 months intended for active master's and Ph.D. students.
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.
- 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.
Nice To Haves
- Familiarity with Vector Databases or Large Language Models (LLMs) is a plus.
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.
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What This Job Offers
Job Type
Part-time
Career Level
Entry Level
Number of Employees
501-1,000 employees
