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Research Scientist
1 month ago
Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps and services like Messenger, Instagram, and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. To apply, click "Apply to Job" online on this web page.
Research Scientist Responsibilities
- Perform research and develop solutions to computer software and computer hardware problems.
- Research, design, and develop new optimization algorithms and techniques to improve the efficiency and performance of Meta's platforms.
- Design and implement large-scale distributed software systems to serve large numbers of complex requests simultaneously and without failure.
- Utilize technical research background, train new ranking models, and run experiments.
- Create tools for migrating large bodies of user data across systems for new products, scalability efforts, and development of new core infrastructure.
- Use machine learning, statistics, or other data techniques to build algorithms.
- Suggest, collect, and synthesize system requirements from stakeholders and create effective feature roadmaps.
- Analyze and resolve computer challenges from a system engineering standpoint.
- Work on problems of diverse scope where analysis of data requires evaluation of identifiable factors.
- Demonstrate good judgment in selecting methods and techniques for obtaining solutions.
- Requires a PhD degree in Computer Science, Electrical and Computer Engineering Engineering, Information Systems, Analytics, Statistics, Mathematics, Physics, Applied Sciences, or a related field. Requires completion of a university-level course, research project, internship, or thesis in the following:
- Algorithms, data structures, or systems software
- Solving analytical problems using quantitative approaches
- Gathering, manipulating, or analyzing complex, high-volume, high-dimensionality data from varying sources
- Communicating complex research in a clear, precise, and actionable manner
- Research in topics closely related to machine learning, NLP, recommendation systems, pattern recognition, signal processing, data mining, artificial intelligence, information retrieval, or computer vision
- Performing research that enables learning the semantics of data (images, video, text, audio, or other modalities) and advances the technology of intelligent machines
- Devising better data-driven models of human behavior
- Adapting standard machine learning methods to best enterprise modern parallel environments: distributed clusters, multicore SMP, or GPU
- Developing highly scalable classifiers and tools leveraging machine learning, statistics, regression, rules-based models, or mathematical models
- Java, C++, Perl, PHP, or Python.
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