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.
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. We’re seeking to hire a Machine Learning Engineer with a strong track record for building and deploying production-quality ML models to build out our ML infrastructure as our organization grows to serve millions of students.
- We understand the challenges schools face - we intimately understand the challenges faced by schools because our founding team spent years working in schools/districts. We take pride in our team, which includes dedicated educators, social workers, and experienced administrators. Together, we work closely with schools every day, aiming to maximize our impact.
- We are dedicated to impact - We've supported renowned, impact focused organizations such as the National Science Foundation, US Department of Education, NewSchools Venture Fund, and Digital Promise. With their support and our unwavering commitment, we've invested significantly in research to ensure that our product creates a meaningful and positive impact within schools and classrooms.
- We are passionate about equity - The majority of STG’s school and district partners serve predominantly low-income communities, which have been historically underserved. Our product is thoughtfully designed to close gaps rather than create them, and ensures that every student has an equal opportunity to thrive.
- We’re small, but mighty - Our tight-knit, agile group is driven by a shared aspiration to make a difference while building a successful business. With team members who have experience working at large, influential organizations such as Meta, IBM, Capital One, and Palantir, we are determined to create a scalable product that impacts millions of students positively.
We're seeking individuals who embody the following qualities:
- Passion for Impact: We're not just another tech company – we're driven by a deep commitment to making a meaningful difference in the lives of students. If you're passionate about creating positive change and empowering the next generation, you're in the right place.
- Comfort in Ambiguity: In a dynamic start-up environment, change is constant, and the path forward isn't always clear-cut. We're looking for team members who thrive in uncertainty, can craft a strategy on the fly, and execute with confidence and autonomy.
- Sense of Urgency: Time is of the essence in a start-up. If you're someone who enjoys the thrill of moving fast and building with purpose, you'll find our culture both exhilarating and rewarding.
- Aspiration for Growth: While you may have experience at larger organizations, you're ready for a new challenge that offers more responsibility and an opportunity to shape the future. We're here to provide that platform for your professional growth.
- Design innovative solutions for machine learning infrastructure that will support the current and future needs of the company’s products
- Build robust systems and 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
- 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 workflows, preferably using platforms such as Databricks and MLflow
- Programming experience with Python and Spark 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 )
- 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 Databricks