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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 COMMUNITY 

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.

 

THE ROLE

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, GraphQL, 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, and guided by our Engineering Principles. You can read about our latest work on our Engineering Blog. 

 

A few highlights:

• 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

 

WHAT YOU BRING

Required

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, related field, or equivalent professional experience.
• 5 years of Software Engineering experience, including significant time working with large ML datasets
• Strong programming skills in Go, Python, SQL, and at least one data pipeline framework (e.g., Airflow, Dagster, Prefect).
• Experience with data versioning tools (e.g., DVC, LakeFS) and cloud storage systems.
• Familiarity with machine learning workflows — from training data preparation to evaluation.
• Familiarity with the architecture and operation of large language models, and a nuanced understanding of their capabilities and limitations.
• Attention to detail and an obsession with data quality and reproducibility.

 

Preferred

• Experience with labeling platforms (e.g., Label Studio, Scale AI, Toloka) or human-in-the-loop systems.
• Understanding of ML evaluation techniques, including prompt-based and generative model metrics.
• Exposure to MLOps practices such as model registry, feature store, or continuous evaluation.
• Background in education technology or other human-centered AI applications.

 

PERKS AND BENEFITS

We may be a non-profit, but we reward our talented team extremely well! We offer:

• Competitive salaries
• Ample paid time off as needed – Your well-being is a priority
• 8 pre-scheduled Wellness Days in 2026 occurring on a Monday or a Friday for a 3-day weekend boost
• Remote-first culture - that caters to your time zone, with open flexibility as needed, at times
• Generous parental leave
• An exceptional team that trusts you and gives you the freedom to do your best
• The chance to put your talents towards a deeply meaningful mission and the opportunity to work on high-impact products that are already defining the future of education
• Opportunities to connect through affinity, ally, and social groups
• And we offer all those other typical benefits as well: 401(k) + 4% matching & comprehensive insurance, including medical, dental, vision, and life

 

At Khan Academy, we are committed to fair and equitable compensation practices, the well-being of our employees, and our Khan community. This belief is why we have built out a robust Total Rewards package that includes competitive base salaries, and extensive benefits and perks to support physical, mental, and financial well-being.

The compensation band for this role is $137,871 - $172,339 USD annually for candidates based in the United States and $186,306 - $232,883 CAN annually for candidates based in Canada.

The pay range for this position is a general guideline only. The salary offered will depend on internal pay equity and the candidate’s relevant skills, experience, qualifications, and job market data. Additional incentives are provided as part of the complete total rewards package, in addition to comprehensive medical and other benefits.

 

As part of our hiring process, we use a secure identity verification service through CLEAR® (in partnership with Greenhouse) to confirm that each applicant is who they claim to be. CLEAR® provides a safe, consistent way to confirm identity, helping protect both applicants and the company from impersonation or fraud. Read more about it here.

MORE ABOUT US

• Sal’s TED talk from 2011
• Sal’s TED talk from 2015
• Sal's TED talk from 2023
• Our team: