Staff Research Scientist, User Modeling and Personalization
$229,000–$343,000 year
On-siteBellevue, Washington, United States
Job Summary
Formulate and derive a research agenda in user modeling and personalization, including generative modeling, recommendation systems, and information retrieval. Partner with engineering teams to translate research into business impact for real-world ML applications used by millions. Build scalable research prototypes and evaluate them in large-scale machine learning scenarios. Share expertise with teammates and interns, and publish findings at top conferences. Join the User Modeling and Personalization Research Team at Snap Inc., working on generative and language models for information retrieval and efficient large-scale recommender systems.
Required 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
Desired 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
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