Data Scientist II - Computer Vision

Overview

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 AI and deep learning techniques to revolutionize geospatial analysis and derive insight from imagery and location data. We are passionate about applying data science and artificial intelligence to solve some of the worlds biggest challenges.

Our team develops tools, APIs, and AI models for geospatial analysts and data scientists, enabling them to leverage the latest research in spatial data science, AI and geospatial deep learning.

As a Data Scientist, you will develop deep learning models using libraries such as PyTorch and create APIs and tools for training and deploying them on satellite imagery. If you are passionate about deep learning applied to remote sensing and GIS, developing AI and deep learning models, and love maps or geospatial datasets/imagery, this is the place to be!

Responsibilities
 Develop tools, APIs and pretrained models for geospatial AI
 Integrate ArcGIS with popular deep learning libraries such as PyTorch
 Develop APIs and model architectures for computer vision and deep learning applied to geospatial imagery
 Author and maintain geospatial data science samples using ArcGIS and machine learning/deep learning libraries
 Curate and pre/post-process data for deep learning models and transform it into geospatial information
 Perform comparative studies of various deep learning model architectures

Requirements
 2+ years of experience with Python, in data science and deep learning
 Self-learner with coursework in and extensive knowledge of machine learning and deep learning
 Experience with Python machine learning and deep learning libraries such as PyTorch, Scikit-learn, NumPy, Pandas
 Expertise in one or more of the following areas:
 Traditional and deep learning-based computer vision techniques with the ability to develop deep learning models for computer vision tasks (image classification, object detection, semantic and instance segmentation, GANs, super-resolution, image inpainting, and more)
 Convolutional neural networks such as VGG, ResNet, Faster R-CNN, Mask R-CNN, and others
 Transformer models applied to computer vision
 Expertise in 3D deep learning with Point Clouds, meshes, or Voxels with the ability to develop 3D geospatial deep learning models, such as PointCNN, MeshCNN, and more
 Experience in data visualization in Jupyter Notebooks using matplotlib and other libraries
 Experience with hyperparameter-tuning and training models to a high level of accuracy
 Bachelor's in computer science, engineering, or related disciplines from IITs and other top-tier engineering colleges
 Existing work authorization for India

Recommended Qualifications
 Experience applying deep learning to satellite or medical imagery or geospatial datasets
 Familiarity with ArcGIS suite of products and concepts of GIS

About Esri

At Esri, diversity is more than just a word on a map. When employees of different experiences, perspectives, backgrounds, and cultures come together, we are more innovative and ultimately a better place to work. We believe in having a diverse workforce that is unified under our mission of creating positive global change. We understand that diversity, equity, and inclusion is not a destination but an ongoing process. We are committed to the continuation of learning, growing, and changing our workplace so every employee can contribute to their lifes best work. Our commitment to these principles extends to the global communities we serve by creating positive change with GIS technology. For more information on Esris Racial Equity and Social Justice initiatives, please visit our website here.

If you dont meet all of the preferred qualifications for this position, we encourage you to still apply!


Esri Privacy Esri takes our responsibility to protect your privacy seriously. We are committed to respecting your privacy by providing transparency in how we acquire and use your information, giving you control of your information and preferences, and holding ourselves to the highest national and international standards, including CCPA and GDPR compliance.,