Research Scientist, Language For Personalization (AI)

TL;DR

Research Scientist, Language for Personalization (AI): Inventing new ways to model user behavior and build user-centric ML systems, shaping personalized experiences across Snap with an accent on generative and language models, large-scale recommender systems, and graph data representation. Focus on inventing technology to deliver customized experiences and collaborating with engineering teams to deliver technology to millions of hirify.globalters.

Location: Must work in an office 4+ days per week.

Salary: $173,000-$259,000 (Zone A, CA, WA, NYC), $164,000-$246,000 (Zone B), or $147,000-$220,000 annually (Zone C). Position is eligible for equity in the form of RSUs.

Company

Snap Inc. is a technology company that believes the camera presents the greatest opportunity to improve the way people live and communicate.

What you will do

• Lead research projects in user modeling and personalization, including generative modeling, recommendation systems, information retrieval, and efficiency.
• Build scalable research prototypes and evaluate them in large-scale machine learning scenarios.
• Share expertise with teammates and interns.
• Publish findings at top conferences.
• Partner with engineering teams to deliver technology to millions of hirify.globalters.

Requirements

• PhD in computer science, machine learning, mathematics, or equivalent practical experience.
• Strong knowledge of machine learning, information retrieval, personalization, and deep learning.
• Demonstrated ability to lead and execute challenging research projects.
• Strong computer science fundamentals and engineering skills (Python, PyTorch).
• Experience applying language models in generative search, ranking, and/or personalization.
• Track record of publications in machine learning, information retrieval, or language venues.

Nice to have

• Experience with large-scale machine learning problems in research or industry.
• Experience with large-scale data processing using machine learning frameworks on cloud solutions like Google Cloud, AWS, and/or Azure.
• Familiarity with post-training, preference optimization, working with large-scale search or recommendation interaction data, and recommender systems.
• Demonstrated ability to transform cutting-edge research into tangible product improvements.

Culture & Benefits

• "Default Together" Policy: Team members are expected to work in an office 4+ days per week.
• Snap Inc. is an equal opportunity employer.
• Comprehensive benefits include paid parental leave, medical coverage, mental health support, and equity.