AI Specialist - Product and Applied Research

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.

AI Specialist - Product and Applied Research Responsibilities:

• Develop highly scalable algorithms based on state-of-the-art machine learning and neutral network methodologies
• Suggest, collect, and synthesize requirements and create effective feature roadmap
• 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 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

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

• 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)