Make a difference. As a Data Engineer specializing in LLM Workflows on the Apps Engineering team, you'll work directly with large-scale datasets by exploring their characteristics, evaluating their quality, and maintaining them throughout the ML development lifecycle. You'll dive deep into data for LLM workflows to understand what makes datasets effective for model training and fine-tuning adapters. Beyond dataset work, you'll design and build web-based tools that support data collection, model evaluation, and result visualization through intuitive interfaces. You'll develop APIs and data pipelines that connect data collection tools with ML training infrastructure, creating seamless workflows for model development and fine-tuning. This role requires strong Python skills for both data analysis and web development, combined with curiosity about machine learning fundamentals and LLM workflows. Experience with data processing and evaluation of LLM workflows. Experience building data collection and evaluation for LLM-supported systems. Experience with developing web tools using JavaScript or TypeScript. Experience deploying web tools or applications on cloud platforms (AWS or GCP). Experience with machine learning fundamentals and frameworks (scikit-learn, PyTorch). BS/MS in Computer Science, Data Engineering, or related technical field, or 3 years of equivalent work experience. Experience exploring and analyzing large-scale datasets for ML applications. Experience with dataset curation, quality assessment, and bias detection methodologies. Experience building data collection tools or working with crowd annotation platforms. Experience designing data augmentation pipelines. Experience with data visualization libraries and creating dashboards for dataset analysis and ML metrics. Experience with model development or LLM fine-tuning pipelines. Experience working with creators, audio/video production, or creative software applications.