5+ years of experience building and scaling data pipelines for machine learning applications at staff or lead engineer level, ideally in research or model training environments
Strong background in data engineering and ML data curation for LLMs, VLMs, or other large-scale multimodal models
Expertise in distributed data systems (e.g., Spark, Hadoop, Ray, or similar) and efficient large dataset processing/ETL workflows
Proven ability to build robust, scalable, and production-grade data infrastructure for ML pipelines
Experience developing tools for data labeling, filtering, deduplication, quality assurance, and dataset management
Strong programming skills (Python, SQL, PySpark, or similar) and familiarity with cloud data platforms (AWS, GCP, Azure)
Knowledge of privacy, compliance, ethics, and best practices in data collection and management
Excellent cross-functional collaboration, problem-solving, and communication skills
Passion for enabling cutting-edge generative AI and creative technology through data excellence