Snap Inc

Staff Research Scientist, User Modeling and Personalization

Snap Inc$229K — $343K *
Consumer Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • PhD in computer science or related technical field with equivalent experience.
  • 5+ years of industry or postdoctoral experience in relevant areas.
  • Strong knowledge of machine learning, information retrieval, and personalization methodologies.
  • Proven track record of publications in top-tier machine learning conferences.
  • Experience with distributed training in multi-node and multi-GPU environments.
  • Hands-on experience with Python and PyTorch for scalable ML development.

Responsibilities

  • Formulate research agendas in user modeling and personalization.
  • Collaborate with engineering teams to apply research in real-world scenarios.
  • Develop scalable prototypes and evaluate their performance in machine learning scenarios.
  • Mentor and share expertise with teammates and interns.
  • Publish research findings at prominent conferences.

Benefits

  • Paid parental leave for family needs.
  • Comprehensive medical benefits to support health.
  • Emotional and mental health support programs available.
  • Compensation packages including long-term equity options.
Full Job Description
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 youll 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 "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.  : Snap Inc. is its own community, so weve 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 Snaps 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 candidates 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. 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.

About Snap Inc

Snap Inc. is a camera and social media company. It was founded in 2011 by Evan Spiegel, Bobby Murphy, and Reggie Brown. The company is known for its Snapchat app, which allows users to send photos and videos that disappear after being viewed. Snap Inc. is headquartered in Santa Monica, California and has offices around the world. The company went public in 2017 and is listed on the New York Stock Exchange.
Learn more about Snap Inc
Size
5,661 employees
Market Cap
$13.9 billion
Industry
Net Income
-$944.8 million
Founded
2016
5 Year Trend
+59.1%
Revenue
$2.5 billion
NASDAQ

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