Researcher – Pretraining Data Team

Overview

In this role, you will join the Pre-training Data team to design and curate large-scale datasets powering frontier AI models. You will work with scientists, engineers, and annotators to ensure data quality, ethics, and impact on model development. You’ll craft data collection strategies, build scalable ingestion and annotation pipelines, and evaluate data-driven model behaviors. This cross-disciplinary position emphasizes responsible AI and practical improvements to models and products.

Responsibilities

• Create high-quality datasets for training and evaluation and run data ablations to measure impact
• Develop and maintain scalable data pipelines for ingestion, processing, filtering, and annotation
• Analyze real-world datasets to assess quality, diversity, relevance, and identify improvements
• Build lightweight tools and workflows for dataset auditing, visualization, and versioning
• Collaborate with Safety, Ethics, and Governance teams to meet quality, privacy, and responsible AI standards

Key requirements

• Bachelor’s Degree in AI, Computer Science, Data Science, Statistics, Physics, Engineering, or related technical discipline AND 4+ years of technical engineering experience with Python and data libraries (Pandas, NumPy) OR equivalent experience
• 2+ years of data analysis or data engineering with large-scale datasets (unstructured or semi-structured)
• Proficiency in statistics and exploratory data analysis
• Familiarity with data processing frameworks such as Spark, Ray, or Apache Beam
• Ability to communicate technical findings to research and product teams
• Equivalent experience options for higher degrees as stated in the ad

• Strong communication and ability to explain complex results to diverse audiences
• Cross-functional collaboration with researchers, engineers, and governance teams
• Analytical mindset with attention to data quality and ambiguity
• Python
• Pandas
• NumPy

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