Data Engineer - LLM Workflows

Requirements

• 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).

Nice to Haves

• 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.

What You'll Be Doing

• Work directly with large-scale datasets for LLM workflows.
• Explore dataset characteristics, evaluate quality, and maintain data throughout the ML development lifecycle.
• Design and build web-based tools supporting data collection, model evaluation, and result visualization.
• Develop APIs and data pipelines connecting data collection tools with ML training infrastructure.
• Use Python skills for data analysis and web development, combined with knowledge of machine learning fundamentals and LLM workflows.