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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.
Job Responsibility:
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
Develop and study the performance of large-scale machine learning models
Work collaboratively with engineers to deploy machine learning models in production
Requirements:
Master's degree (or foreign equivalent) in Computer Science, 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