Research Intern, User Modeling and Personalization

About the role

We are looking for a Research Scientist Intern 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 structured data modeling, recommendation systems, and large-scale machine learning.

Responsibilities

• Lead research projects in the user modeling and personalization domains (sub-areas include graph modeling, generative recommendation, personalization, and ML efficiency)
• Build scalable research prototypes and evaluate them in large-scale machine learning scenarios
• Publish your findings at top conferences

Requirements

• Currently enrolled in a PhD program in a technical field such as computer science, machine learning, statistics, mathematics, or equivalent years of experience
• Track record of (co-)first-author publications in top machine learning, data mining, information retrieval or language venues (e.g. KDD, WSDM, SIGIR, RecSys, ACL, ICLR, NeurIPS, COLM etc.)
• Strong familiarity with ML libraries such as PyTorch, Tensorflow, Jax or related frameworks
• Experience with distributed (multi-GPU, or multi-node) model training, inference and experimentation; experience with large-scale settings in academic/industrial research labs is a plus

Skills

• Strong technical knowledge of state-of-the-art ML algorithms in one or more above sub-areas
• Demonstrated ability in defining, leading and executing challenging research projects
• Strong computer science fundamentals, problem-solving and engineering skills
• Proven ability to mentor interns, students and junior researchers

Preferred Qualifications

• Experience with large-scale machine learning in an academic or industrial research lab, or equivalent open-source experience
• Experience with distributed data processing and machine learning frameworks on Enterprise Cloud solutions like Google Cloud, AWS, and/or Azure
• Familiarity with language models and generative recommendation and retrieval
• Demonstrated ability to transform cutting-edge research into tangible product improvements
• Specialization and hands-on experience with state-of-the-art recommendation models and scalable machine learning technologies

Schedule

At Snap Inc. we practice a “default together” approach and expect our team members to work in an office 4+ days per week.

Benefits

• Paid parental leave
• Comprehensive medical coverage
• Emotional and mental health support programs
• Compensation packages that let you share in Snap’s long-term success

Pay

In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position.

• Zone A (CA, WA, NYC): $81,000-$121,000 annually
• Zone B: $77,000-$115,000 annually
• Zone C: $69,000-$103,000 annually