AI/ML Engineer

Job Description:

Hi All,

We are Hiring for AI/ML Engine

AI/ML Engineer responsible for building core ML infrastructure that powers adaptive learning for 100K+ students 

Develop recommendation engines, predictive analytics, computer vision, and NLP systems using Python, TensorFlow, and PyTorch.

Task:

• Design and train ML models for student behavior prediction and content recommendation
• Build recommendation systems, personalizing study plans for 100K+ active learners
• Develop predictive models for exam readiness, dropout risk, and performance forecasting
• Implement MLOps pipelines for automated model training, validation, and deployment
• Create NLP systems for content analysis and computer vision models for document processing
• Design data pipelines for collecting and processing educational data from MongoDB and PostgreSQL
• Build real-time analytics systems for tracking learning progress and engagement patterns

Preferred Skills:

• 3+ years of machine learning engineering experience with production ML systems deployment
• Strong proficiency in Python and ML libraries: scikit-learn, PyTorch, TensorFlow, XGBoost
• Experience with MLOps tools and practices: MLflow, model versioning, automated training
• Solid understanding of statistical analysis, feature engineering, and A/B testing
• Experience with data engineering and database management: MongoDB and PostgreSQL

• Experience in EdTech, learning analytics, or educational data mining
• Knowledge of recommender systems, personalization algorithms, and collaborative filtering
• Familiarity with deep learning for NLP and computer vision applications
• Experience with real-time ML systems, streaming data processing, and API development

• Knowledge of cloud ML services: AWS SageMaker, Google AI Platform, or Huawei Cloud
• Experience with containerization (Docker) and model deployment in production
• Understanding of Progressive Web App integration and React.js frontend ML features
• Knowledge of privacy-preserving ML techniques: differential privacy, federated learning

• Passionate about using machine learning to solve educational challenges and improve outcomes
• Strong engineering mindset focused on scalable, maintainable ML systems
• Data-driven decision maker balancing model complexity with practical constraints
• Excellent problem-solving skills for ambiguous, research-oriented problems
• Strong communication skills to explain complex ML concepts to non-technical stakeholders
• Self-motivated individual with the ability to take ownership of ML projects from conception to deployment