Staff Research Scientist, User Modeling and Personalization

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