This role pays less than
98%
of similar roles. Most pay
$205,000–$260,150
— the shaded band above.
At the midpoint, this role pays about
$101k
versus about
$233k
for comparable roles.
Based on 240 similar postings.
Employer
About Snap Inc.
Snap Inc. is a technology and camera company, best known for Snapchat, offering visual communication, augmented reality, and advertising products.
Snap Inc. currently has
76 open roles
on FindRole.
Listed pay typically runs
$209,000–$313,000
across 58 roles with salary data.
Research Intern, User Modeling and Personalization joins the User Modeling and Personalization Research Team to innovate ways to model user behavior and build user-centric machine learning systems. The role involves leading research projects in areas such as graph modeling, generative recommendation, personalization, and ML efficiency while building scalable prototypes for large-scale machine learning scenarios. Candidates will be expected to publish findings at top conferences. Key technical requirements include proficiency with PyTorch, TensorFlow, or Jax, along with experience in distributed multi-GPU or multi-node training and inference. The work focuses on solving problems in structured data modeling and recommendation systems to deliver customized experiences. Preferred skills include familiarity with language models, generative retrieval, and experience with enterprise cloud solutions like Google Cloud, AWS, or Azure to transform cutting-edge research into tangible product improvements within the personalization domain.
Lead research projects in user modeling, graph modeling, generative recommendation, and ML efficiency.
Build scalable research prototypes for large-scale machine learning scenarios.
Evaluate research findings and publish them at top-tier academic conferences.
Develop advanced models to improve personalized experiences across Snap platforms.
Translate cutting-edge research into tangible product improvements.
Mentor interns, students, and junior researchers within the team.
What we're looking for
Must be currently enrolled in a PhD program in a technical field or possess equivalent experience.
Must have a track record of (co-)first-author publications in top machine learning, data mining, information retrieval, or language venues.
Must possess strong technical knowledge of state-of-the-art ML algorithms in areas like graph modeling, generative recommendation, and personalization.
Must have strong computer science fundamentals, problem-solving skills, and engineering capabilities.
Must be familiar with ML libraries such as PyTorch, TensorFlow, Jax, or related frameworks.
Must have experience with distributed multi-GPU or multi-node model training, inference, and experimentation.
Preferred experience includes large-scale machine learning in academic/industrial labs or via open-source projects.
Preferred experience includes distributed data processing on enterprise cloud solutions like Google Cloud, AWS, or Azure.
Machine Learning
Python
PyTorch
Information Retrieval
Recommender Systems
Representation Learning
Graph Data
Google Cloud
AWS
Azure
Data Processing
Generative Modeling
Machine Learning
PyTorch
JAX
TensorFlow
Agentic Systems
ML Modeling
Prototyping
Research and Development
Large-scale Systems
iOS
iPadOS
macOS
watchOS
visionOS
Machine Learning
PyTorch
JAX
TensorFlow
Agentic Systems
ML Modeling
Prototyping
Research and Development
Large-scale Systems
iOS
iPadOS
macOS
watchOS
visionOS