Research Scientist

3 weeks ago

Menlo Park, United States Meta Platforms, Inc. Full time

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 algorithms and models based on state-of-the-art machine learning advancements, especially in the areas of natural language processing (NLP)/computational linguistics, speech synthesis and scientific computing.

Contribute to the research-to-production efforts that advance Meta's products and services hosted on large-scale distributed systems.

Work on research projects, strategies, and problems of moderate to high complexity and scope, which requires research skills and deep domain knowledge in order to define long term objective with short and medium term sub-tasks as milestones.

Use quantitative research methods to define, iterate upon, and advance key areas of research agenda.

Can identify and define both short and medium term objectives.

Independently identify, motivate, and execute on medium to large hypotheses (each with many tasks) for model improvements through data analysis, and domain knowledge, and are able to communicate your learnings effectively.

Influence progress of relevant research communities by producing publications.

Utilize technical research background, train new machine/deep learning models, and run numerical/quantitative experiments.

Create tools and workflow that for end-to-end data pipeline that facilitate data-driven machine learning solution development, including data acquisition, pre-/post-processing and curation often at large scales.

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.

Drive team goals and technical direction to pursue opportunities that make the larger organization more efficient by serving as a subject-matter with deep and state-of-the-art knowledge in machine learning.

Independently research and implement state-of-the-art machine learning models and techniques on PyTorch, TensorFlow or other platforms.

Minimum Qualifications

* Requires a Ph.D. degree in Computer Science/Engineering, Computational Science/ Engineering, Information Systems, Analytics, Statistics, Mathematics, Physics, Applied Sciences, or a related field OR completion of all coursework towards a PhD degree in Computer Science/Engineering, Computational 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:



1. Algorithms, data structures, or systems software

2. Solving analytical problems using quantitative approaches

3. Gathering, manipulating, or analyzing complex, high-volume, high-dimensionality data from varying sources

4. Communicating complex research in a clear, precise, and actionable manner

5. Research in topics closely related to machine learning, NLP, recommendation systems, pattern recognition, signal processing, data mining, artificial intelligence, information retrieval, or computer vision

6. Performing research that enables learning the semantics of data (images, video, text, audio, or other modalities) and advances the technology of intelligent machines

7. Devising better data-driven models of human behavior

8. Adapting standard machine learning methods to best enterprise modern parallel environments: distributed clusters, multicore SMP, or GPU

9. Developing highly scalable classifiers and tools leveraging machine learning, statistics, regression, rules-based models, or mathematical models

10. Java, C++, Perl, PHP, or Python.

Locations

About Meta

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps 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. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today-beyond the constraints of screens, the limits of distance, and even the rules of physics.

Meta is committed to providing reasonable support (called accommodations) in our recruiting processes for candidates with disabilities, long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support. If you need support, please reach out to accommodations-ext@fb.com.

$214,032/year to $240,240/year + bonus + equity + benefits

Individual pay is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base salary, Meta offers benefits. Learn more about benefits at Meta.

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