Nucleus

Role Overview

Nucleus AI is seeking an AI / ML Data Scientist to help 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.

If you enjoy turning real-world data into models that are used by real users—and iterating on them in production—this role is for you.

Key Responsibilities

Machine Learning & Modeling

• Design, develop, and deploy machine learning models that power:
  
   
  • Personalized learning paths
    
     
  • Content and course recommendations
    
     
  • Learner analytics and insights
    
     
  • Adaptive assessments and feedback
    
     
• Build models for:
  
   
  • Learner skill inference and knowledge tracing
    
     
  • Engagement, completion, and drop-off prediction
    
     
  • Automated assessment scoring and feedback
    
     

Data & Analytics

• Analyze large-scale learner behavior data to extract actionable insights
  
   
• Develop and maintain data pipelines, feature engineering workflows, and model evaluation frameworks
  
   
• Apply statistical analysis and experimentation (including A/B testing) to validate model performance and impact
  
   

Collaboration & Product Integration

• Work closely 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
  
   

LLMs & Advanced Techniques

• Experiment with and integrate LLMs and NLP techniques for:
  
   
  • Content generation
    
     
  • Learner feedback
    
     
  • Intelligent learner support
    
     
• Monitor models in production for performance, bias, and drift, and continuously improve them
  
   

Documentation & Governance

• Document models, assumptions, experiments, and results to ensure transparency, reproducibility, and maintainability
  
   

Required Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, AI/ML, Statistics, or a related field
  
   
• Strong proficiency in Python and common ML libraries (e.g., scikit-learn, PyTorch)
  
   
• Solid understanding of:
  
   
  • Supervised and unsupervised learning
    
     
  • Feature engineering and model evaluation
    
     
  • Statistical analysis and experimentation
    
     
• 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 Qualifications

• Experience building ML systems in ed-tech, LMS platforms, or learning analytics
  
   
• Familiarity with:
  
   
  • Large Language Models (LLMs)
    
     
  • NLP
    
     
  • Recommendation systems
    
     
  • Knowledge graphs
    
     
• Experience deploying models to production environments
  
   
• Exposure to cloud platforms such as AWS, GCP, or Azure
  
   
• Understanding of learning science, instructional design, or assessment theory
  
   
• Experience with MLOps tools (model versioning, monitoring, CI/CD for ML)
  
   

What We Offer

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