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:
- Formulate and derive a research agenda in the user modeling and personalization domains, including generative modeling, recommendation systems, information retrieval, and efficiency
- Partner with engineering teams to translate research to business impact for real-world ML applications used by millions of Snapchatters
- 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
Knowledge, Skills, & Abilities:
- Strong technical knowledge of machine learning, information retrieval, personalization, language 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 computer science, machine learning, language technologies or related technical field such as statistics, mathematics, or equivalent years of experience
- 5+ years of industry or postdoctoral experience
- Track record of publications in top machine learning, information retrieval or language venues (e.g. ICLR, NeurIPS, ICML, KDD, RecSys, SIGIR, WSDM, ACL, COLM, etc.)
- Experience with distributed (multi-node and multi-GPU) ML model training, inference and experimentation
- Experience applying language models in the context of generative search, ranking and/or personalization
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
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 $229,000-$343,000 annually.
Zone B:
The base salary range for this position is $218,000-$326,000 annually.
Zone C:
The base salary range for this position is $195,000-$292,000 annually.
This position is eligible for equity in the form of RSUs.
