Member of Technical Staff AI Data Platform Frontier Models

What you'll do

• Develop and evolve large-scale AI data infrastructure for pre-training and post-training workloads at the exabyte scale.
• Build automated systems for processing multimodal data including text, images, video, and documents.
• Design and train models for classification, recognition, captioning, and quality scoring to improve data processing.
• Create intelligent data pipelines using LLMs and agents to automate collection, filtering, deduplication, and annotation.
• Architect AI-optimized storage layers using formats like Lance, Iceberg, and Parquet to support multimodal embeddings.
• Source and create high-value datasets for specialized domains through human annotation and synthetic data generation.
• Execute a data-model-evaluation loop by analyzing model failures to identify and fill specific data gaps.

What we're looking for

• Master's degree in Computer Science, Math, Software Engineering, Computer Engineering, or a related field and 3+ years of relevant experience.
• Bachelor's degree in Computer Science, Math, Software Engineering, Computer Engineering, or a related field and 4+ years of relevant experience.
• Proficiency in Python with experience in SQL and Shell.
• Experience with distributed data platforms such as Spark, Flink, or Ray.
• Hands-on experience building datasets for LLM/VLM/multimodal model pre-training or post-training.
• Experience with synthetic data generation including text, image-text synthesis, and multimodal trajectory generation.
• Experience with open file and table formats such as Lance, Iceberg, Paimon, and Parquet.
• Experience building ETL systems, data models, data pipelines, or data warehouses (preferred).