AI/ML Developer

Major Duties and Responsibilities

1. Model Development and Implementation

• Design, develop, and optimize machine learning models for forecasting, risk analysis, and decision support
• Implement predictive models for hazard detection, impact estimation, and early warning systems

2. Data Engineering and Processing

• Collect, clean, and preprocess large datasets including meteorological, hydrological, and geospatial data
• Develop data pipelines for real-time and batch data processing

3. Integration with DSS and IBF Systems

• Integrate AI/ML models into web-based decision support systems and operational platforms
• Collaborate with full stack developers and GIS experts to embed analytics into dashboards and applications

1. Model Deployment and MLOps

• Deploy models using APIs and containerized environments
• Implement monitoring, logging, and performance tracking for deployed models
• Ensure reproducibility, scalability, and reliability of AI/ML solutions

5. Advanced Analytics and Innovation

• Explore and implement advanced techniques such as deep learning, ensemble modeling, and uncertainty quantification
• Support development of impact-based forecasting methodologies using AI/ML approaches

6. Documentation and Capacity Building

• Prepare technical documentation, model reports, and user guidelines
• Conduct training and knowledge transfer sessions for internal teams and stakeholders

7. Additional Responsibilities

• Perform other tasks as assigned by the supervisor in line with project needs and priorities.

Deliverables:

• Deployed AI/ML models integrated into DSS platforms
• Clean, structured, and version-controlled datasets and code repositories
• Model performance reports and validation results
• APIs and services enabling model integration with applications
• Technical documentation and training materials
• Periodic progress reports aligned with project timelines