Senior Platform Engineer, ML Data Systems (24 months fixed-term) at Khan Academy

Mountain View, California, United States -

Full Time

Start Date

Immediate

Expiry Date

06 Mar, 26

Salary

172339.0

Posted On

06 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Engineering, Data Science, Programming, ETL Pipelines, Data Quality, Data Governance, Cloud Storage, Data Versioning, Human Labeling, Data Normalization, Data Enrichment, Collaboration, Documentation, MLOps, Education Technology

Industry

E-Learning Providers

Description

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, or a related field. 5 years of Software Engineering experience with 3+ of those years working with large ML datasets, especially those in open-source repositories such as Hugging Face 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. Motivated by the Khan Academy mission “to provide a free world-class education for anyone, anywhere." Proven cross-cultural competency skills demonstrating self-awareness, awareness of other, and the ability to adopt inclusive perspectives, attitudes, and behaviors to drive inclusion and belonging throughout the organization. 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 target salary range for this position is $137,871 - $172,339 USD / $186,306 - $232,883 CAN. 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. MORE ABOUT US Sal’s TED talk from 2011 Sal’s TED talk from 2015 Sal's TED talk from 2023 Our team: http://www.khanacademy.org/about/the-team OUR COMPANY VALUES Live & breathe learners We deeply understand and empathize with our users. We leverage user insights, research, and experience to build content, products, services, and experiences that our users trust and love. Our success is defined by the success of our learners and educators. Take a stand As a company, we have conviction in our aspirational point of view of how education will evolve. The work we do is in service to moving towards that point of view. However, we also listen, learn and flex in the face of new data, and commit to evolving this point of view as the industry and our users evolve. Embrace diverse perspectives We are a diverse community. We seek out and embrace a diversity of voices, perspectives and life experiences leading to stronger, more inclusive teams and better outcomes. As individuals, we are committed to bringing up tough topics and leaning into different points of view with curiosity. We actively listen, learn and collaborate to gain a shared understanding. When a decision is made, we commit to moving forward as a united team. Work responsibly and sustainably We understand that achieving our audacious mission is a marathon, so we set realistic timelines and we focus on delivery that also links to the bigger picture. As a non-profit, we are supported by the generosity of donors as well as strategic partners, and understand our responsibility to our finite resources. We spend every dollar as though it were our own. We are responsible for the impact we have on the world and to each other. We ensure our team and company stay healthy and financially sustainable. Bring out the joy We are committed to making learning a joyful process. This informs what we build for our users and the culture we co-create with our teammates, partners and donors. Cultivate learning mindset We believe in the power of growth for learners and for ourselves. We constantly learn and teach to improve our offerings, ourselves, and our organization. We learn from our mistakes and aren’t afraid to fail. We don't let past failures or successes stop us from taking future bold action and achieving our goals. Deliver wow We insist on high standards and deliver delightful, effective end-to-end experiences that our users can rely on. We choose to focus on fewer things — each of which aligns to our ambitious vision — so we can deliver high-quality experiences that accelerate positive measurable learning with our strategic partners. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, gender, gender identity or expression, national origin, sexual orientation, age, citizenship, marital status, disability, or Veteran status. We value diversity, equity, and inclusion, and we encourage candidates from historically underrepresented groups to apply. As part of this commitment, Khan Academy will ensure that persons with disabilities are provided reasonable accommodations for the hiring process. If reasonable accommodation is needed, please contact careers@khanacademy.org

Responsibilities

The role involves evolving and maintaining pipelines for transforming raw trace data into ML-ready datasets and collaborating with various teams to ensure data quality. You will also be responsible for implementing automated tests and contributing to data governance strategies.