Are you passionate about applying AI and machine learning to solve some of the world’s biggest challenges? So are we! Esri is the world leader in geographic information systems (GIS) and developer of ArcGIS, the leading mapping and analytics software used in 75 percent of Fortune 500 companies. At the Esri R&D Center-New Delhi, we are applying cutting-edge deep learning techniques to revolutionize geospatial analysis and derive insight from imagery and location data.
Join our team of exceptional data scientists and software engineers to deliver a spatial data science platform, develop industry-leading AI models for satellite imagery, and build world-class Geo AI solutions.
In this role, you will apply geospatial analysis, data science, and machine learning to geospatial problems. You will author Jupyter Notebooks that showcase ArcGIS AI capabilities and advocate patterns to solve such problems. You will gain valuable experience on how to test and develop deep learning models, APIs, and Geo AI solutions.
- Author and maintain Jupyter Notebook-based geospatial data science samples using ArcGIS and machine learning/deep learning libraries such as Tensorflow and PyTorch
- Execute API tests using the continuous integration pipeline and test automation framework
- Enhance test automation framework to test and compare AI models using appropriate evaluation metrics
- Author, maintain, and update unit tests and test assets and help maintain high QA standards
- Certify AI models and APIs ahead of product release cycles
- 1+ years of experience with Python programming
- Coursework and knowledge of machine learning and deep learning
- Knowledge of GIS tools, libraries, and capabilities
- Experience with Python machine learning and deep learning libraries such as Scikit-learn, Pandas, PyTorch/FastAI, or TensorFlow/Keras
- Experience with continuous integration and QA testing
- Strong verbal and written communication skills
- Bachelor's or master's in sciences, engineering, GIS, or related disciplines
- Familiarity with ArcGIS suite of products and concepts of GIS, including working with ArcGIS API for Python
- Experience with technical writing and teaching
- Knowledge of various scientific libraries such as SciPy, R, Numpy, Matlab, etc.