Seeking engineers and researchers to join the Pretraining Text Data team to build the next generation of foundation large language models. The role focuses on designing and curating high-quality datasets, developing novel data collection strategies, improving dataset quality and integrity, understanding data-driven model behaviors, training models on data impact, and aligning datasets with ethical and societal values. This is a cross-disciplinary, high-impact role at the intersection of data and innovation.

This role focuses on building and optimizing training data pipelines and evaluation frameworks for audio models, with a secondary focus on model tuning and deployment. The engineer will be responsible for data sourcing, cleaning, labeling, QA, versioning, and lineage, as well as developing evaluation frameworks and driving continuous quality improvements. They will also optimize training and inference performance for latency, throughput, cost, and reliability.