AI / ML Data Scientist

Nucleus AI is seeking an AI/ML Data Scientist to build and scale an AI-backed Learning Management System (LMS) that delivers personalized, adaptive learning experiences. This is a hands-on, product-focused role at the intersection of machine learning, data science, and learning technology. You will design and deploy intelligent systems that directly impact learner engagement, personalization, assessment, and outcomes.

• Design, develop, and deploy machine learning models powering personalized learning paths, content recommendations, learner analytics, and adaptive assessments
• Build models for learner skill inference, knowledge tracing, engagement prediction, and automated assessment scoring
• Analyze large-scale learner behavior data and develop data pipelines, feature engineering workflows, and model evaluation frameworks
• Conduct statistical analysis and A/B testing to validate model performance and impact
• Collaborate with product managers, engineers, and instructional designers to translate learning objectives into AI-driven solutions
• Integrate models into production systems via APIs, batch pipelines, or real-time inference
• Experiment with LLMs and NLP techniques for content generation, learner feedback, and intelligent support
• Monitor models in production for performance, bias, and drift
• Document models, assumptions, experiments, and results for transparency and reproducibility

• Bachelor's or Master's degree in Data Science, Computer Science, AI/ML, Statistics, or related field
• Strong proficiency in Python and common ML libraries (scikit-learn, PyTorch)
• Solid understanding of supervised and unsupervised learning, feature engineering, model evaluation, and statistical analysis
• Experience working with both structured and unstructured data
• Proficiency in SQL and working with large datasets
• Ability to clearly communicate complex technical concepts to non-technical stakeholders
• Nice-to-have: Experience in ed-tech or learning analytics, familiarity with LLMs and NLP, recommendation systems, knowledge graphs, production model deployment, cloud platforms (AWS, GCP, Azure), learning science background, or MLOps tools experience

Benefits & Perks:

• Opportunity to work on mission-driven AI that improves how people learn
• Ownership of ML systems used by real learners at scale
• Collaborative, cross-functional team culture
• Competitive compensation and benefits
• Flexible work location and schedule
• Continuous learning and professional growth opportunities