AI Research Scientist, Language - Generative AI

Meta•New York, NY

6d•$154,000 - $217,000

About The Position

Meta is seeking a Research Scientist to join its Llama Large Language Model (LLM) Research team. The role is for a recognized expert in NLP or reinforcement learning, with experience in areas such as LLM alignment, multilingual modeling, code generation, responsible AI, or model controllability. The position focuses on producing and applying new science to develop and responsibly release large language models. The Research Scientist will lead and conduct research advancing large language models, contribute directly to experiments and research outputs, and work with a large, globally distributed team. The role also includes identifying ambitious research goals and milestones, prioritizing work applicable to Meta product development, mentoring team members, and supporting healthy cross-functional collaboration.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
PhD in AI, computer science, or a related technical field.
Experience holding an industry, faculty, or government researcher position.
Publications in machine learning.
Experience writing software and executing complex experiments involving large AI models and datasets.
Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.

Nice To Haves

Direct experience in generative AI and LLM research.
Experience developing and debugging in Python.
First-author publications at peer-reviewed AI conferences such as NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL.
At least 2 years of work experience in a university, industry, or government lab in a role primarily focused on AI research.

Responsibilities

Lead, collaborate on, and execute research that advances the state of the art in large language model research.
Contribute directly to experiments by designing experimental details, writing reusable code, running evaluations, and organizing results.
Work with a large and globally distributed team.
Contribute to publications and open-sourcing efforts.
Identify long-term ambitious research goals and intermediate milestones.
Prioritize research that can be applied to Meta's product development.
Mentor other team members and contribute significantly to healthy cross-functional collaboration.