Job Description

We’re looking for an ML Data Engineer to evolve our eval dataset tools to meet the growing platform needs of AI-based tutoring at Khan Academy. You will gather internal requirements, design schema, deploy, document, and train people on an internal dataset management framework.

Responsibilities

• Evolve and maintain pipelines for transforming raw trace data into ML-ready datasets
• Clean, normalize, and enrich data while preserving semantic meaning and consistency
• Prepare and format datasets for human labeling, and integrate results into ML datasets
• Develop and maintain scalable ETL pipelines using Airflow, DBT, Go, and Python running on GCP
• Implement automated tests and validation to detect data drift or labeling inconsistencies
• Collaborate with AI engineers, platform developers, and product teams to define data strategies
• Contribute to shared tools and documentation for dataset management and AI evaluation
• Inform data governance strategies for proper data retention, PII controls/scrubbing, and isolation of sensitive data

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field
• 5 years of Software Engineering experience with 3+ years working with large ML datasets
• Strong programming skills in Go, Python, SQL, and at least one data pipeline framework
• Experience with data versioning tools and cloud storage systems
• Familiarity with machine learning workflows
• Familiarity with the architecture and operation of large language models
• Attention to detail and an obsession with data quality and reproducibility
• Motivated by the Khan Academy mission
• Proven cross-cultural competency skills

Benefits

• No benefits