Qualification:
- 4 years of relevant work experience in Deep learning, Machine learning and expertise with statistical data analysis such as linear models, multivariate analysis, stochastic models, sampling methods.
- Previous exposure in handling GIS data and large raster files
- Experience in GCP
- Strong python programming experience
- Good to have experience in GDAL and Rasterio
- Experience in building Computer Vision workflows
- Previous exposure in deploying production ready ML / DL pipelines using Tensorflow / Pytorch.
- Applied experience with machine learning on large datasets.
Responsibilities:
- Implement Computer Vision modules for different problem statements and follow best practises in ML/ DL
- Work on GIS data and build inferences out of satellite imagery
- Read state of the art research papers and come up with solutions to apply computer vision / ML in the domain of remote sensing
- Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
- Build and prototype analysis pipelines iteratively to provide insights at scale. Develop comprehensive knowledge of kawa data structures and metrics, advocating for changes where needed for product development.
- Research and develop analysis, forecasting, and optimization methods to improve the quality of Kawa’s user facing products.
