Language Research Scientist

Responsibilities

• check_circle Design, implement, and optimize LLM-based agents for a variety of applications, leveraging the latest advances in generative AI
• check_circle Apply reinforcement learning algorithms to improve LLM performance, safety, and alignment
• check_circle Integrate models and orchestrations in production
• check_circle Collaborate with cross-functional teams (research, engineering, product) to deploy and evaluate LLM agents in real-world scenarios
• check_circle Analyze and interpret experimental results, iterate on model architectures, and drive continuous improvement
• check_circle Contribute to the broader AI/ML community at Meta through knowledge sharing, code reviews, and technical mentorship
• check_circle 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

Basic qualifications

• 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)
• Good 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

Preferred qualifications

• Experience with RLHF, reward modeling, or other LLM 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

About the company