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knowledai
knowledai cover picture
Founded :
2024
Type :
Products & Services
Size :
0-20
Stage :
Bootstrapped

About

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Jobs at knowledai

knowledai
at knowledai
Knowled ai
Posted by Knowled ai
Bengaluru (Bangalore)
6 - 8 yrs
₹7L - ₹8L / yr (ESOP available)
skill iconAngularJS (1.x)
skill iconPython
DevOps
skill iconData Analytics
PDF

Key Responsibilities

🖥️ Frontend (Angular)

  • Develop responsive, accessible web UI for assessment tools, educator dashboards, and parent reports.
  • Implement dynamic form builders and scoring interfaces for multiple domains (reading, writing, math).
  • Build PDF report previews, filtering tools, and real-time updates.

🔙 Backend (Python/FastAPI)

  • Design and implement APIs for user management, assessments, intervention logs, and reports.
  • Integrate scoring logic and data aggregation for AI insights.
  • Implement secure role-based access (admin, educator, parent).

🛠️ DevOps / Systems

  • Maintain scalable architecture with PostgreSQL / MongoDB, Docker, and deployment pipelines.
  • Work with AI engineer to connect ML models to backend for prediction and recommendation layers.
  • Optimize performance and ensure data security (GDPR-aligned).


Read more
knowledai
at knowledai
Knowled ai
Posted by Knowled ai
Remote, Bengaluru (Bangalore)
3 - 5 yrs
₹5L - ₹6L / yr
Artificial Intelligence (AI)
Generative AI

Key Responsibilities

🧪 AI/ML Research & Development

  • Develop AI models to identify learning difficulty patterns based on multi-domain assessments.
  • Train models to classify LD categories (e.g., dyslexia, dysgraphia) from scoring + qualitative inputs.
  • Build recommendation logic for intervention strategies based on child profiles and educator feedback.

📊 Data Processing & Pipeline

  • Design data pipelines to preprocess structured and semi-structured data (scores, observations, logs).
  • Work with educator-generated reports and build logic to convert qualitative insights into ML-readable formats.

🔎 Model Evaluation & Iteration

  • Perform evaluation using accuracy, recall, precision; but also focus on interpretability and ethical AI.
  • Use techniques like SHAP, attention weights, or decision trees for explainability in recommendations.

🤝 Collaboration & Integration

  • Work closely with frontend/backend teams to integrate AI insights into the assessment tool UI.
  • Sync with special educators to validate model predictions and continuously improve the output quality.


Read more
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