Research Scientist, Language Personalization

Overview

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’s three core products are Snapchat
, a visual messaging app that enhances your relationships with friends, family, and the world;
Lens Studio
, an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses,
Spectacles
.

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.

We seek to redefine the state-of-the-art in technology to deliver our users customized experiences which delight them.

• 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

• 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

• 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.)

• 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 interaction data, and recommender systems

• Demonstrated ability to transform cutting-edge research into tangible product improvements

If you have a disability or special need that requires accommodation, please don’t be shy and provide us some information
.

"Default Together" Policy at Snap:
At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a “default together” approach and expect our team members to work in an office 4+ days per week.

At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color,…