Machine Learning Engineer

Who We Are

NWEA® is a division of Houghton Mifflin Harcourt that supports students and educators through research, assessment solutions, policy and advocacy services, professional learning and school improvement services that fight for equity, drive classroom impact and push for systemic change in our educational communities. For nearly 50 years, NWEA has developed innovative pre-K–12 assessments, including their flagship interim assessment, MAP® Growth™ and their reading fluency and comprehension assessment, MAP® Reading Fluency™. For more information, visit NWEA.org to learn more.

What you will do

The Machine Learning Engineer (ML engineer) contributes to the design, development, and deployment of real-world Machine Learning systems that facilitate and accelerate advanced AI solutions at scale. Machine Learning Engineers manage aspects of the Machine Learning pipeline, including sourcing and preparing data, building, and training models, and deploying to and monitoring models in production.

Responsibilities

• Manage, maintain, scale, and improve Machine Learning models already running in production environments.
• Design, test, and deploy models to production, initially as a prototype, and then as an API that can serve predictions for end users.
• Design, run, and evaluate Machine Learning tests and experiments.
• Optimize and tweak Machine Learning models according to how they behave in production.
• Use CI/CD processes throughout the model development lifecycle to develop higher quality code and models without disruption to production. 
• Provide technical support to data and product teams, helping relevant parties use and understand Machine Learning systems and datasets.