AI Stack Developer

You will be responsible for developing AI and ML models, designing scalable data workflows, building APIs, and collaborating with various teams to implement technical solutions in the field of climate resilience, agriculture, hydrology, and rural livelihoods. - **AI ML Model Development**: - Design, develop, and optimize machine learning models such as computer vision, time-series forecasting, geospatial ML, and NLP applications. - Build end-to-end ML pipelines for model training, validation, deployment, and monitoring using multisource datasets like remote sensing, weather, IoT sensors, and operational databases. - **Data Engineering Architecture**: - Develop scalable data workflows for ingestion, transformation, and storage. - Integrate heterogeneous datasets including geospatial, tabular, imagery, streaming sensor data into AI-ready DBMS. - Utilize cloud platforms like AWS, Azure, GCP for compute and data management. - **Application API Development**: - Build APIs and microservices to integrate ML models with existing platforms. - Contribute to web and mobile application modules that leverage AI-generated insights. - **Collaboration Cross-functional Support**: - Collaborate closely with researchers, geoinformatics analysts, agronomists, and field teams to translate real-world needs into technical solutions. - Support pilot testing, iterative refinement, and deployment of AI-enabled features in field settings. **Required Qualifications Skills Education**: - Bachelors or Masters degree in Computer Science, Data Science, AI, ML, or related field. **Technical Skills**: - Strong foundation in Python. - Working knowledge of JavaScript and TypeScript is a plus. - Familiarity with AI ML Frameworks like TensorFlow, PyTorch, scikit-learn, XGBoost, OpenCV. - Experience with Data Engineering using SQL, NoSQL databases, PostgreSQL, PostGIS preferred. - Knowledge of ETL workflows, cloud storage, DevOps, MLOps, Docker, Git, GitHub, CI/CD pipelines, model serving frameworks like FastAPI, Flask, TorchServe, ONNX, MLflow. - Visualization experience with dashboards. **Nice-to-have Skills**: - Experience deploying ML models in production environments or mobile/web applications. - Geospatial Remote Sensing experience with Google Earth Engine, GDAL, Sentinel, Landsat data processing. This role requires 2-3 years of experience, and exceptional freshers with solid AI portfolios may also apply. The Watershed Organisation Trust (WOTR) is a non-profit organization committed to rural development, climate resilience, and ecosystem-based adaptation. If you are passionate about leveraging AI technology to address real-world challenges and contribute to sustainable solutions, apply by sending your application to careers@wotr.org with the subject line "AI Stack Developer." You will be responsible for developing AI and ML models, designing scalable data workflows, building APIs, and collaborating with various teams to implement technical solutions in the field of climate resilience, agriculture, hydrology, and rural livelihoods. - **AI ML Model Development**: - Design, develop, and optimize machine learning models such as computer vision, time-series forecasting, geospatial ML, and NLP applications. - Build end-to-end ML pipelines for model training, validation, deployment, and monitoring using multisource datasets like remote sensing, weather, IoT sensors, and operational databases. - **Data Engineering Architecture**: - Develop scalable data workflows for ingestion, transformation, and storage. - Integrate heterogeneous datasets including geospatial, tabular, imagery, streaming sensor data into AI-ready DBMS. - Utilize cloud platforms like AWS, Azure, GCP for compute and data management. - **Application API Development**: - Build APIs and microservices to integrate ML models with existing platforms. - Contribute to web and mobile application modules that leverage AI-generated insights. - **Collaboration Cross-functional Support**: - Collaborate closely with researchers, geoinformatics analysts, agronomists, and field teams to translate real-world needs into technical solutions. - Support pilot testing, iterative refinement, and deployment of AI-enabled features in field settings. **Required Qualifications Skills Education**: - Bachelors or Masters degree in Computer Science, Data Science, AI, ML, or related field. **Technical Skills**: - Strong foundation in Python. - Working knowledge of JavaScript and TypeScript is a plus. - Familiarity with AI ML Frameworks like TensorFlow, PyTorch, scikit-learn, XGBoost, OpenCV. - Experience with Data Engineering using SQL, NoSQL databases, PostgreSQL, PostGIS preferred. - Knowledge of ETL workflows, cloud storage, DevOps, MLOps, Docker, Git, GitHub, CI/CD pipelines, model serving frameworks like FastAPI, Flask, TorchServe, ONNX, MLflow. - Visualization experience with dashboards. **Nice-to-have Skills**: - Experience deploying ML models in