Machine Learning Engineer
1 month ago
Responsibilities:
- Designing and Development of an automated Crop Model, based on crop calendar and signature bank from optical, microwave, and hyperspectral satellite images and field data.
- Responsible for forecasting harvest date and amount along with signature identification and crop estimation through automated crop model.
- Development of automated Disease/pesticide Model.
- Model compatibility with Web-based GIS.
- Responsible for designing and developing a Web-based GIS portal for supporting search engine, query generation, and output generation from Remote Sensing Crop Model
- Creating and managing RASTER & VECTOR data layer in the database i.e., weather data, soil moisture, growth data, soil temperature, for better forecasting and decision-making for potential yield, and disease management.
- Creating and managing web GIS applications system.
- Designed, develop, and optimize computer vision algorithms for various models and applications, such as object detection, image segmentation, facial recognition, tracking, and 3D reconstruction, Remote sensing, Agriculture field.
- Implement computer vision models and techniques using popular libraries and frameworks, such as OpenCV, TensorFlow, PyTorch, or other deep learning platforms.
- Conduct experiments, evaluate model performance, and fine-tune algorithms to achieve desired accuracy and efficiency.
- Optimize computer vision pipelines for real-time performance and deploy models to production environments.
Skill:
- Good communication and coordination skills are required.
- Target-oriented working methodology.
- Proficiency in Python, Matlab, other programming languages, and AI-ML.
- Geo-server, Open layer, PostgreSQL, post-gis, Open-source GIS & RS Software.
- JAVA Script, Advance JAVA, JASON, Python, PHP, etc.
- Educational Qualification:
MSc. Or M.Tech, B.Sc. or B.Tech in remote sensing/Geoinformatics/ Agriculture IT, IT.
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