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Research Scientist, Central Applied Science, Privacy-Preserving ML - New York, United States - Meta Platforms, Inc.
Description
Central Applied Science establishes state-of-the-art scientific advancements for Meta's products and systems. The team's expertise spans many domains including AI/ML, statistics, economics, network science and mathematical optimization.We own tooling and libraries, develop methodologies, design and prototype solutions, and partner across Meta to launch these solutions such that 3 billion people and 10 million advertisers can benefit.
We seek Research Scientists to identify new opportunities and help build scientifically rigorous systems focused on enabling new capabilities and improved performance.
This role focuses on Meta's large scale machine learning and analytics systems for Meta's products across Facebook, Instagram, WhatsApp, Messenger, and Reality Labs.
Our team's applied research includes incorporating approaches such as differential privacy for large scale model training, designing effective attacks, and evaluating practical risks in various applications including recommendation systems and generative models.
We also pursue advancements in federated learning and on-device processing, where client-side applications include recommender systems for advertising and organic content, generative AI experiences, models, text prediction, and scene understanding.
Research Scientist, Central Applied Science, Privacy-Preserving ML (PhD) ResponsibilitiesDerive theoretical formulations when necessary.
Implement new algorithms or mechanisms, deploy them into internal or open-sourced libraries and tooling platforms, and conduct empirical studies on internal datasets to showcase value for real world applications.
Currently has, or is in the process of obtaining, a PhD degree in Computer Science, Statistics, Mathematics, relevant technical field, or equivalent practical experience.
Proficiency designing and implementing analytical and/or algorithmic solutions, tailored to particular business needs and tested on large data sets.
Proficiency with at least one of the following technologies: (i) Differential Privacy, (ii) Privacy Attacks and Auditing for ML model risks, (iii) Federated Learning, (iv) On-Device Model Personalization.
Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.
Experience in training, fine-tuning, and/or experimenting with foundation models beyond black-box use.
Familiarity with one or more deep learning frameworks (e.g. PyTorch, TensorFlow, etc.).
Proficiency in C or C++.
Experience working and communicating cross-functionally in a team environment.
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.
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.
