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Reality Labs Research is Meta’s innovation engine for next-generation AR/VR, AI, and wearable technologies. Our Audio team pioneers research and development at the intersection of sound, machine learning, and human experience—enabling new ways for people to connect, communicate, and collaborate. We are seeking a technically skilled GenAI scientist to join our team focused on Large Language Model (LLM) agents and model post-training, with a particular emphasis on speech and language processing. This role will be close to product applications and user impact, requiring full-stack knowledge. You will be a technical leader supporting research and product development for AI wearables as part of Meta’s Superhuman Communication & Connection initiative. Your work will focus on building and optimizing ML infrastructure, including data pipelines, model training, evaluation, and validation—leveraging both companywide platforms and developing custom developed project-specific tools. By joining our team, you will have the opportunity to work on breakthrough technologies that redefine how people connect and communicate, collaborate with world-class researchers and engineers in a fast-paced, mission-driven environment, and shape the future of AI wearables and superhuman audio experiences.
Job Responsibility:
Design, implement, and optimize LLM-based agents for a variety of applications, leveraging the latest advances in generative AI
Apply reinforcement learning algorithms to improve LLM performance, safety, and alignment
Integrate models and orchestrations in production
Collaborate with cross-functional teams (research, engineering, product) to deploy and evaluate LLM agents in real-world scenarios
Analyze and interpret experimental results, iterate on model architectures, and drive continuous improvement
Contribute to the broader AI/ML community at Meta through knowledge sharing, code reviews, and technical mentorship
Lead and contribute to research and development of post-training methods, including RLHF (Reinforcement Learning from Human Feedback), reward modeling, and other feedback-based approaches
Apply AI Models to Speech Encoding, Decoding, and Synthesis problems
Develop Natural Language interaction systems
Requirements:
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Artificial Intelligence, Generative AI, or a relevant technical field
Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)
Demonstrated programming skills in Python and familiarity with large-scale distributed training
Familiarity to learn new programming languages quickly
Can design, implement, and evaluate RL algorithms in production or research settings
Problem-solving, communication, and collaboration skills
Nice to have:
Experience with Reinforcement Learning from Human Feedback, reward modeling, or other Large Language Model post-training techniques
Experience working in cross-functional teams
Track record of publications or contributions to open-source projects in LLMs, RL, or related areas
Familiarity with safety, alignment, and evaluation challenges in generative AI
Experience with speech encoding, decoding and synthesis
Experience with natural language processing systems