From making valuable connections between people and businesses to building premium services that deliver high-value experiences, the Monetization organization at Meta empowers people and businesses to succeed in the global economy. As Meta focuses on building the next evolution of social experiences, the Monetization team plays a crucial role in shaping the communication pathways and financial tools that all sized businesses, especially small to medium ones, need to thrive in the new digital economic environment. We achieve that from end-to-end product and technology innovation. As a Machine Learning Research Scientist on the Monetization team at Meta, you can help build cutting-edge full-stack technologies that will transform the way people and businesses connect and communicate. You’ll help develop industry-leading solutions that power next-generation, large-scale platforms and AI services to help connect billions of people around the world.

Research Scientist, Machine Learning for Monetization (PhD) Responsibilities:

• Develop highly scalable classifiers and tools leveraging Machine Learning, data regression, and rules based models.
• Suggest, collect, and synthesize requirements to create an effective feature roadmap.
• Adapt standard Machine Learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).
• Lead and contribute to cutting-edge research that results in industry-leading tech demos and/or publications.
• Collaborate closely with cross-functional partners and contribute towards Meta's research product development.

Minimum Qualifications:

• Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
• Currently has, or is in the process of obtaining, a PhD degree in Machine Learning, Artificial Intelligence, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
• Hands-on experience in Deep Learning algorithms and techniques, e.g., convolutional neural networks (CNN), transformers, quantization, data efficient learning, or similar.
• Experience with Python, C++, or Java, and scripting languages such as Perl, Python, PHP, shell scripts, or similar.
• Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.

Preferred Qualifications:

• Demonstrated research and software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICML, ICLR, AAAI, or similar.
• Experience working and communicating cross-functionally in a team environment.
• Experience on Data Efficient Learning, domain adaptation, Semi-supervised Learning, etc.
• Exposure to architectural patterns of large scale software applications.
• Experience manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources.
• Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.

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.