Research Scientist, AI Language

Meta•Menlo Park, CA

1d•$184,000 - $257,000

About The Position

Meta is seeking a Research Scientist to advance natural language processing and large language model research within Meta Superintelligence Labs. The role conducts foundational and applied research in language understanding, generation, reasoning, and alignment, contributing to next-generation language models for Meta's AI products and services at global scale. The scientist drives high-impact research from conception through publication and production integration, collaborating with researchers and engineers to shape language AI.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
At least 8 years of research or industry experience in natural language processing, large language models, or a closely related area of machine learning.
Experience leading complex, multi-stage research projects from problem definition through publication or production deployment.
Track record of publications at peer-reviewed NLP or machine learning conferences such as ACL, EMNLP, NAACL, NeurIPS, ICML, or ICLR.
Hands-on experience training, fine-tuning, or evaluating large language models using frameworks such as PyTorch.
Experience communicating research findings and technical decisions in writing to research and engineering audiences, including through design documents and technical reports.

Nice To Haves

Experience bridging foundational language model research with production systems, including model evaluation at scale and staged rollout using feature flagging and A/B testing frameworks.
Experience designing and curating large-scale pretraining or fine-tuning datasets, including data quality filtering, deduplication, and domain mixing strategies.
Experience with large-scale distributed language model training across hundreds or thousands of GPUs, including optimization of training stability and throughput.
Research contributions in reasoning, instruction following, reinforcement learning from human feedback, or model alignment and safety.

Responsibilities

Design and execute original research on large language models, including post-training, instruction tuning, reasoning, alignment, agentic tool calling, and evaluation.
Develop novel architectures, training objectives, and data curation strategies to improve language model capabilities and reliability.
Lead end-to-end research projects, including problem formulation, experimental design, analysis, and communication of findings to technical and non-technical stakeholders.
Build and maintain evaluation frameworks and benchmarks to measure language model performance across diverse tasks and domains.
Collaborate with engineering, product, and policy partners to translate research advances into production language AI systems.
Improve training pipelines, data quality, and model efficiency through instrumentation, profiling, and systematic experimentation.
Mentor researchers and engineers on language model research methodology and best practices.
Use AI-assisted tools and workflows to accelerate research iteration, code quality, and cross-disciplinary collaboration.