Key Responsibilities: - Design and operate large-scale data pipelines supporting AI training, evaluation, and continual improvement workflows. - Build ingestion systems for multimodal data including text, image, audio, video, and structured signals. - Implement data cleaning, deduplication, filtering, and quality assurance at petabyte scale. - Develop dataset versioning, lineage, and provenance tracking for reproducible training. - Build high-throughput data loading systems that maximize GPU utilization during training. - Implement labeling workflows, active learning pipelines, and human-in-the-loop data improvement systems. - Design storage architectures balancing cost, throughput, and latency across data tiers. - Build evaluation dataset construction pipelines with data integrity and contamination controls. - Implement data privacy, redaction, and consent enforcement throughout the pipeline. - Collaborate with ML researchers and engineers to align data systems with model development needs. - Drive o

Key Responsibilities: - Design and operate large-scale data pipelines supporting AI training, evaluation, and continual improvement workflows. - Build ingestion systems for multimodal data including text, image, audio, video, and structured signals. - Implement data cleaning, deduplication, filtering, and quality assurance at petabyte scale. - Develop dataset versioning, lineage, and provenance tracking for reproducible training. - Build high-throughput data loading systems that maximize GPU utilization during training. - Implement labeling workflows, active learning pipelines, and human-in-the-loop data improvement systems. - Design storage architectures balancing cost, throughput, and latency across data tiers. - Build evaluation dataset construction pipelines with data integrity and contamination controls. - Implement data privacy, redaction, and consent enforcement throughout the pipeline. - Collaborate with ML researchers and engineers to align data systems with model development needs. - Drive o