AI Specialist - Product and Applied Research

About Meta

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. 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 proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.

Responsibilities of an AI Specialist - Product and Applied Research at Meta

• Develop highly scalable algorithms based on state-of-the-art machine learning and neural network methodologies.
• Suggest, collect, and synthesize requirements, then create effective feature roadmaps.
• Code deliverables in tandem with the engineering team.
• Adapt standard machine learning methods to best exploit modern parallel environments (e.g., distributed clusters, multicore SMP, and GPU).
• Perform specific responsibilities which vary by team.
• Research, design, and develop new algorithms and techniques to improve the efficiency and performance of Meta's platforms.
• Gather data for machine-learning training, train new ranking models, and run experiments.
• Identify potential improvements in the company's software and technology products.
• Research and present effects of current engineering efforts on Meta's market standing from an economic and game-theoretic point of view.
• Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules-based models.

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• Research and/or work experience in machine learning, NLP, reinforcement learning, deep learning, recommendation systems, pattern recognition, signal processing, data mining, artificial intelligence, information retrieval, or computer vision.
• Proficiency in Java, C++, Perl, PHP, or Python.

Preferred Qualifications

• PhD in Computer Science, Computer Engineering, or relevant technical field.
• Experience with developing scalable machine learning models in at least one of the following areas: Crawling, indexing, extraction, retrieval, ranking, recommendations, measurement, tooling, evaluation, query understanding, planning, vector databases, or embeddings.
• Experience with large-scale model training, implementing algorithms, and evaluating speech-based systems.
• Experience taking ideas from research to production.
• Experience solving complex problems and comparing alternative solutions, tradeoffs, and broad points of view to determine a path forward.
• Experience working and communicating cross-functionally in a team environment.
• First author publications experience at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL).

Key skills/competency

• Machine Learning
• Deep Learning
• Natural Language Processing (NLP)
• Reinforcement Learning
• Computer Vision
• Data Mining
• Scalable Algorithms
• Neural Networks
• Distributed Systems
• Python/Java/C++