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We're looking for an engineer to join our small, high-impact team responsible for architecting and scaling the core infrastructure behind distributed training pipelines, multimodal data catalogs, and intelligent processing systems that operate over petabytes of data.

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As a software engineer on our data infrastructure team, you'll design, build, and operate scalable, fault-tolerant infrastructure for LLM Research: distributed compute, data orchestration, and storage across modalities. You'll develop high-throughput systems for data ingestion, processing, and transformation , including training data catalogs, deduplication, quality checks, and search. You'll also build systems for traceability, reproducibility, and robust quality control at every stage of the data lifecycle.

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You'll collaborate with research teams to unlock new features, improve data quality, and accelerate training cycles. You'll implement and maintain monitoring and alerting to support platform reliability and performance.

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If you're excited by distributed systems, large-scale data mining, open-source tools like Spark, Kafka, Beam, Ray, and Delta Lake, and enjoy building from the ground up, we'd love to hear from you.

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XML job scraping automation by YubHub

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