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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.
- Develop and study the performance of large-scale machine learning models.
- Work collaboratively with engineers to deploy machine learning models in production.
Minimum Qualifications
- 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
- Java, C++, Perl, PHP, or Python
$268,011/year to $297,550/year + bonus + equity + benefits
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