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.
