Senior Machine Learning Engineer
About Us
At Teachers Pay Teachers (TpT), we’re unlocking the power of educator-created content. More than 2 out of 3 of U.S. teachers come to TpT every year to get teacher-tested, engaging, and rigorous materials. What began as a humble exchange for teachers looking to share lesson plans has since exploded into an education powerhouse where teachers have created more than 3 million resources for all aspects of PreK-12 education. More than five million educators worldwide (including teachers, administrators, and parents) have downloaded TpT resources more than a billion times. If you haven’t heard of TpT yet and want to learn more, just talk to a teacher about us. Or try this recent article in Forbes.
Role
As a Sr. Machine Learning Engineer at TpT you will be working with data scientists, data engineers, software engineers, and our product team to create production data products, including categorization, prediction, and recommender systems. You’ll be fitting models, designing, building and scaling services, and building tools to ensure quality and a great experience for our users.
Qualities for a successful candidate
- Strong experience with development of predictive models in production in industry, ideally in Python.
- Experience with building, scaling, and monitoring resilient software systems.
- Comfortable with both research and back-end software development in a fast-paced, dynamic environment.
- Strong statistics and mathematics background, including linear algebra.
- Enjoys working collaboratively with peer engineering teams.
- Mentors teammates and teaches what you’ve learned.
- At least four years of data science/machine learning experience in industry.
Extra Points for
- Experience with Ed-Tech and on-line marketplaces.
- Experience with Docker/Kubernetes, Spark, or AWS at scale.
- Experience with R, including Shiny applications.
- Experience with search systems and information retrieval.
- Experience with Natural Language Processing.
- Degree in Computer Science, Data Science, or equivalent experience.
- Open Source or professional community contributions.