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Research Scientist, Language Personalization

Job in Santa Monica, Los Angeles County, California, 90403, USA
Listing for: SNAP, Inc.
Full Time position
Listed on 2026-10-17
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, Data Scientist, AI Engineer (Applied/Software), AI Business & Operations
  • Research/Development
    Data Scientist, AI Business & Operations
Salary/Wage Range or Industry Benchmark: 173000 - 259000 USD Yearly USD 173000.00 259000.00 YEAR
Job Description & How to Apply Below
Position: Research Scientist, Language for Personalization

Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together.

The Company operates Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world, and Specs Inc., a wholly-owned subsidiary dedicated to making computing more human, in addition to Bitmoji, Saturn, and other digital services.

Snap Research serves as an innovation engine for the company. Our projects range from solutions to hard technical problems that significantly enhance Snap’s existing products, to riskier explorations that can lead to fundamental paradigm shifts in the way people communicate and express themselves. The team consists of scientists and engineers who experiment with and invent new technology that has a lasting impact on Snap’s products.

We also frequently publish our work at top conferences and journals in computer science and related fields.

We are looking for a Research Scientist to join our User Modeling and Personalization Research Team! Our team’s mission is to invent new ways to model user behavior, and empower our business partners to build world-class user‑centric ML systems which shape personalized experiences across Snap. Our work spans the domains of generative and language models for information retrieval, efficient large‑scale recommender systems, and representation learning for structured graph data.

Together with you, we seek to redefine the state‑of‑the‑art in technology to deliver our users customized experiences which delight them.

What you’ll do:
  • Lead research projects in the user modeling and personalization domains, including generative modeling, recommendation systems, information retrieval, and efficiency
  • Build scalable research prototypes and evaluate them in large‑scale machine learning scenarios
  • Share your expertise with teammates and interns
  • Publish your findings at top conferences
  • Partner with engineering teams to deliver your technology to millions of Snap chatters
Knowledge, Skills, & Abilities:
  • Strong technical knowledge of machine learning, information retrieval, personalization, and state‑of‑the‑art deep learning literature
  • Demonstrated ability in defining, leading and executing challenging research projects
  • Strong computer science fundamentals, problem-solving and engineering skills (Python, PyTorch)
  • Pragmatic, hands‑on approach to research with a drive to build working prototypes rather than solely rely on theoretical exploration
  • Proven ability to mentor interns, students and junior researchers
Minimum Qualifications:
  • PhD in a related technical field such as computer science, machine learning, or mathematics or equivalent years of practical work experience
  • Strong familiarity with PyTorch, and hands‑on experience with distributed (multi-node and multi‑GPU) machine learning model training, inference and experimentation
  • Experience applying language models in the context of generative search, ranking and/or personalization
  • Track record of publications (first-author preferred) in top machine learning, information retrieval or language venues (e.g. ICLR, NeurIPS, ICML, KDD, Rec Sys, SIGIR, WSDM, ACL, COLM, etc.)
Preferred Qualifications:
  • Experience with large‑scale machine learning problems in an academic or industrial research lab, or equivalent open‑source experience
  • Experience with large‑scale data processing, collection or synthesis using machine learning frameworks on Enterprise Cloud solutions like Google Cloud, AWS, and/or Azure
  • Familiarity with post‑training, preference optimization, working with large‑scale search or recommendation…
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