Meta is seeking a Research Engineer to join the Fundamental AI Research (FAIR) team, a research organization focused on advancing the state-of-the-art in AI and personal superintelligence. Based in Meta Superintelligence Labs (MSL) within the FAIR, you'll directly contribute to Meta's frontier model, while having the chance to collaborate with researchers and engineers across MSL.
Responsibilities
Perform research to advance the science and technology of intelligent machines
• Develop and scale post-training pipelines for LLMs, including implementation of novel alignment algorithms
• Build engineering infrastructure to evaluate frontier models with regard to alignment and societal impact
• Develop and scale novel applications of pro-social artificial intelligence
• Work towards long-term research goals, while identifying immediate milestones
• Influence progress of relevant research communities by producing publications
• Open source high quality code and produce reproducible research
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
• Research background in machine learning, artificial intelligence, computational statistics, applied mathematics, or related areas
• Research publications reflecting experience in theoretical or empirical research
• Experience in developing and debugging in Python or similar programming languages
• Experience in analyzing and collecting data from various sources, including Hive, Spark, SQL etc
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
Preferred Qualifications
• Experience with large-scale model training, fine-tuning, and post-training (e.g., RLHF, DPO)
• Engineering expertise in distributed systems and deep learning frameworks (e.g., PyTorch)
• Research and engineering experience demonstrated via grants, fellowships, patents, internships, work experience, and/or coding competitions
• First-authored publications at peer-reviewed conferences, such as ICML, NeurIPS, ACL, EMNLP, ICLR, FacCT, CCS, IEEE S&P, and other similar venues
• Experience solving complex problems and comparing alternative solutions, tradeoffs, and different points of view to determine a path forward
• Experience collaborating in a team environment on research projects
• Experience communicating research for public audiences of peers
• Recognized expert in identified research areas such as AI alignment and post-training of Large Language Models (LLMs)
• Keen interest in producing new science to understand intelligence and technology towards ensuring the positive societal impact of artificial intelligence
