Civil Maps is looking for a Machine Learning Architect to join their team of engineers developing the next generation of machines to tackle challenges in data analysis and computation of spatial data. Using deep learning and the Berkeley supercomputer, Civil Maps extracts meaningful geospatial data at scale. We're looking for a self-motivated individual to work side by side our computer vision experts to scale our data pipeline by orders of magnitude.
RESPONSIBILITIES:
-Improving MapReduce framework for processing massive point cloud datasets
Developing management tools for computer vision algorithm development and release
-Formalizing training/testing framework
-Packaging tests for regression analysis
-Releasing algorithms into production
-Building tools for visualizing and comparing algorithm results
-Building tools for QC management
-Building feedback tools for integrating false positives/negatives back into algorithm training
Developing the delivery of data to customers
-spatial databases (project specific, user specific)
-global asset databases
-setting up geoservers behind LBs