Build and refine NLP/ML models over large volumes of unstructured student and educator text, using both classical approaches (feature engineering, classification, CNNs, ensemble methods) and modern LLM-based techniques where they're the right tool.
Partner with data science, product, and engineering to identify, define, and test opportunities to improve the product through ML/NLP — from turning existing models into user-facing features to prototyping entirely new capabilities.
Extend our models beyond 'proof of concept' scope: new reflection prompts, younger students etc, widening accessibility while protecting accuracy.
Design and apply LLMs responsibly for generative and assistive features — for example, contextualized teacher-response suggestions, and resource recommendations — with careful attention to prompting, retrieval, grounding, evaluation, and guardrails.
Build validation, monitoring, and retraining pipelines in partnership with the ML engineering team — including data-drift detection — so models keep performing as code and data change.
Undertake preprocessing of structured and unstructured data, and build reliable, reproducible feature and evaluation workflows.

Bachelor's or higher degree in Computer Science, Data Science, Machine Learning, Math, Statistics, or a related field.
2+ years of experience as a Data Scientist, ML Engineer, or Data Engineer, solving real-world problems with machine learning.
Strong proficiency in Python and the ML stack (pandas, numpy, scikit-learn; PyTorch or TensorFlow; Spark a plus).
Experience building and deploying ML solutions that involve natural language processing of text data.
Working knowledge of core ML techniques such as classification, clustering, prediction, recommender systems, and anomaly detection.
Working knowledge of the complete machine learning lifecycle — data, training, validation, deployment, monitoring, and retraining.
Solid understanding of how modern LLMs work under the hood — transformer architecture, training and fine-tuning, tokenization, embeddings.
Hands-on with at least one of prompting/evaluation, fine-tuning, retrieval-augmented generation (RAG), or agentic/tool-use patterns, with a thoughtful view of when LLMs are and aren't the right approach.
Experience writing and maintaining high-quality production code, and comfort with Git-based workflows.
You care more about curiosity than credentials: you enjoy digging into why a model behaves the way it does, not just what it returns.

Strong interest in working in education technology in an impact-driven, mission-first role.
Experience productionizing ML for real-time, low-latency inference (e.g., AWS SageMaker or comparable), including containerization and CI/CD.
Experience building data-drift detection, model monitoring, and automated retraining systems in partnership with ML engineering teams.
Experience building, training, or fine-tuning language models from the ground up — e.g., implementing transformer components, training or adapting models on domain-specific data, or working with open-weight models beyond off-the-shelf APIs.
Experience with responsible / trustworthy AI: fairness and bias evaluation, privacy-conscious handling of sensitive data, and building guardrails for user-facing generative features.
Experience designing human-in-the-loop evaluation and running online experiments (A/B testing, feature flagging).
Familiarity with the practical, ethical, and legal considerations of working with student data.

Competitive compensation with performance-based incentives and meaningful equity
Comprehensive health and wellness benefits for you and your family
Flexible work arrangements and a genuine commitment to work-life balance
Real pathways for growth — as the platform and the data team expand, so does the scope of this role
A collaborative, mission-driven community where every voice is heard

If you don't check every box, we'd still love to hear from you.
Some of the strongest people on our team grew into parts of their role after they arrived.
Our team is at its best when it reflects the range of students we serve.
If you've taken a less conventional path into this work, or you don't see yourself represented much in tech, we especially hope you'll apply.

Sown To Grow is hiring a Data Scientist (ML / NLP / LLMs)