Senior Platform Engineer, ML Data Systems

ABOUT KHAN ACADEMY

Khan Academy is a nonprofit with the mission to deliver a free, world‑class education to anyone, anywhere. Our proven learning platform offers free, high‑quality supplemental learning content and practice that cover Pre‑K - 12th grade and early college core academic subjects, focusing on math and science. We have over 181 million registered learners globally and are committed to improving learning outcomes for students worldwide, focusing on learners in historically under‑resourced communities.

Our students, teachers, and parents come from all walks of life, and so do we. Our team includes people from academia, traditional/non‑traditional education, big tech companies, and tiny startups. We hire great people from diverse backgrounds and experiences because it makes our company stronger. We value diversity, equity, inclusion, and belonging as necessary to achieve our mission and impact the communities we serve.

We know that transforming education starts in‑house with learning about ourselves and our colleagues. We strive to be world‑class in investing in our people and commit to developing you as a professional.

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. We’re looking for someone who can gather internal requirements, design schema based on well‑known dataset patterns, and deploy, document, and train people on an internal dataset management framework. The systems you design will need to integrate with trace management and human labeling APIs.

You’ll work closely with other AI engineers, platform developers, and labeling teams to ensure our data is clean, representative, and ready for both human and automated evaluation.

This role bridges ML operations, data engineering and data science— enabling our AI systems to learn from reliable, well‑structured datasets that reflect the diversity and nuance of real learners.

As a Platform Engineer focused on dataset management systems
, you will:

• 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 in support of continuously improving the quality of Khan’s AI‑based tutoring.
• Contribute to shared tools and documentation for dataset management and AI evaluation.
• Inform our data governance strategies for proper data retention, PII controls/scrubbing, and isolation of particularly sensitive data such as offensive test imagery.

We are a remote‑first organization, and we strive to build using technology that is best suited to solving problems for our learners. Currently, we build with Go, Graph

QL, JavaScript, React & React Native, Redux and we adopt new technologies like LLMs when they’ll help us better achieve our goals. At Khan, one of our values is "Cultivate Learning Mindsets", so for us, it’s important that we’re working with all of our engineers to help match the right opportunity to the right individual, in order to ensure every engineer is operating at their "learning edge".

Currently, we are focused on providing equitable solutions to historically under‑resourced communities of learners and teachers, guided by our Engineering Principles. You can read about our latest work on our Engineering Blog.

• Incremental Rewrites with GraphQL
• Our Transition to React Native
• Go + Services = One Goliath Project
• How Engineering Principles Can Help You Scale
• How to upgrade hundreds of React components without breaking production

Required

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
• 5 years of Software Engineering experience with 3+ of those years working with large ML datasets, especially those in…