Sown To Grow (STG) is a K12 education technology platform that empowers schools to improve student social, emotional, and academic health through an easy and engaging reflection and feedback process. In a short weekly routine, students check-in emotionally and reflect on the strategies that are working best for them (or new ones to try). They start with a focus on emotional well-being and expand to academic goal-setting over time. Teachers, principals, and counselors understand real-time student emotions with AI-driven insights, and proactively support student needs.

Sown To Grow (STG) is a K12 education technology platform that empowers schools to improve student social, emotional, and academic health through an easy and engaging reflection and feedback process. In a short weekly routine, students check-in emotionally and reflect on the strategies that are working best for them (or new ones to try). They start with a focus on emotional well-being and expand to academic goal-setting over time. Teachers, principals, and counselors understand real-time student emotions with AI-driven insights, and proactively support student needs.

STG has received seed funding from highly selective, innovative funds including the National Science Foundation, US Department of Education, NewSchools Venture Fund, Imagine K12 (now Y Combinator Edtech), Impact Assets, Jane VC, Digital Promise and others. The company currently serves schools in 40 states and has large-scale contracts with organizations such as Metro Nashville Public Schools (TN), Oakland Unified School District (CA), KIPP, and more.

Teachers play a crucial role in STG's process; they are responsible for creating a safe space for students, guiding them on writing reflections, and coaching them on strategies when they get stuck. STG uses natural language processing (NLP) and machine learning (ML) to both quantitatively measure and qualitatively understand student’s social, emotional and academic health. By applying structure to otherwise unstructured text/emotional data, STG seeks to lift up insights for teachers and support students in a scalable way.

The majority of STG’s school and district partners serve predominantly low-income communities. STG is solving high impact and highly relevant problems using students’ academic and social-emotional reflections, making the work technically challenging, ethically nuanced, and fundamentally complex. We are a small, nimble team that is inspired to make a difference in the world while building a successful business. Before starting Sown To Grow, our founding team spent several years working in both the private sector and schools/districts. We care deeply about building a product that positively impacts student outcomes and makes teachers’ lives easier. We’re looking for a Machine Learning Engineer who has a shared belief in these values, an equally strong work ethic, and a track record for building and deploying production-quality ML models.

Responsibilities:

• Design innovative solutions for machine learning infrastructure that will support the current and future needs of the company’s products
• Build validation tools to ensure machine learning models continue to perform as code and data change
• Apply best-practice system software and machine learning knowledge to build scalable, reliable, and easy-to-use machine learning workflows
• Ensure machine learning models can run across multiple platforms on customer machines
• Build infrastructure to perform scalable training, evaluation, inference, debugging, monitoring of the ML/NLP models in the cloud
• Help speed up research and productionization of ML/NLP models and projects

Minimum Qualifications:

• Bachelor's degree or higher degree in computer science or related fields (software engineering or equivalent)
• 2+ years experience as a ML Engineer, Data Engineer or Data Scientist with strong engineering skills and a passion for working on turning reference implementations into production-ready software
• Experience in building, training, deploying and managing large-scale infrastructure for ML solutions
• Programming experience with Python including object-oriented design
• Experience writing and maintaining high-quality production code and using source code control/revision tools (i.e. Git)
• Working knowledge of complete machine learning lifecycle
• Experience in deployment and management of cloud native infrastructure and services with an emphasis on performance and cost optimization (such as AWS, Microsoft Azure, Google Cloud etc )

Preferred Qualifications:

• Strong interest in working in the education technology industry in an impact driven role
• Our data science and machine learning solutions are heavily driven from text data, so either prior experience or interest in learning NLP would be amazing
• Experience working with Amazon Web Services

Ruby on Rails, Python, React, Flask, Machine Learning, Natural Language Processing