Research Scientist, Research

Posted Yesterday
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2 Locations
Hybrid
147K-259K Annually
Entry level
Artificial Intelligence • Cloud • Machine Learning • Mobile • Software • Virtual Reality • App development
Snap is a technology company.
The Role
Lead research in language models, personalization, recommendation systems, information retrieval, and generative modeling. Build scalable machine learning prototypes, conduct large-scale distributed experiments, publish findings, mentor junior researchers and interns, and partner with engineering teams to deploy technologies serving Snapchat users. The role requires strong Python and PyTorch expertise, research leadership, publications, and experience applying language models to search, ranking, or personalization.
Summary Generated by Built In

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 Snapchatters

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, RecSys, 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 interaction data, and recommender systems

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

"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, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets.


We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, where applicable).


Our Benefits: Snap Inc. is its own community, so we’ve got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap’s long-term success!

Compensation

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. These pay zones may be modified in the future.

Zone A (CA, WA, NYC):

The base salary range for this position is $173,000-$259,000 annually.


 

Zone B:

The base salary range for this position is $164,000-$246,000 annually.

Zone C:

The base salary range for this position is $147,000-$220,000 annually.

This position is eligible for equity in the form of RSUs.

If you believe this job description is missing required pay transparency information, please submit a report through this form: Job Description Pay Range Disclosure.

Skills Required

  • PhD in computer science, machine learning, mathematics, or a related technical field, or equivalent practical work experience
  • Strong familiarity with PyTorch
  • Hands-on experience with distributed multi-node and multi-GPU machine learning training, inference, and experimentation
  • Experience applying language models to generative search, ranking, or personalization
  • Publication record in top machine learning, information retrieval, or language venues
  • Large-scale machine learning experience 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 Google Cloud, AWS, or Azure
  • Familiarity with post-training and preference optimization
  • Experience working with large-scale search or recommendation interaction data and recommender systems
  • Ability to transform cutting-edge research into tangible product improvements

What the Team is Saying

Xiaolin
Yvette
Matt
Jasmeet
Xueyin (Sherry)
Amir
Jung
Xu
Talia Mason
Maureen Ufomadu
Vincent Pagnard-Jourdan
Pulkit Trivedi

Snap Inc. Compensation & Benefits Highlights

  • Healthcare Strength — Health coverage includes multiple medical plan options (PPO/HDHP/HMO), dental and vision, HSA/FSA, mental-health support (e.g., Lyra), and wellness programs. Family-building benefits and services like One Medical are also part of the package.
  • Parental & Family Support — Parental leave is described as generous—up to 26–28 weeks for birthing parents and up to 16 weeks for non-birthing parents—alongside adoption, surrogacy, fertility preservation, backup childcare, caregiver assistance, and return-to-work support.
  • Retirement Support — A 401(k) with company match (immediate vesting cited), plus pre-tax, Roth, and after-tax contributions including a Mega Backdoor Roth option, supports long-term savings. Additional financial wellness tools complement the retirement program.

Snap Inc. Insights

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The Company
HQ: Santa Monica, CA
5,000 Employees
Year Founded: 2011

What We Do

We contribute to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together.

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Snap Inc. Teams

Team
Product + Tech
Team
Machine Learning
Team
Sales
About our Teams

Snap Inc. Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Our “default together” approach is an 80/20 model where we are asking team members to spend 80% of the time, on average, in the office, with the remaining 20% of the time spent remote.

Typical time on-site: 4 days a week
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