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Software Development Engineer II

Esri
CompanyEsri
CategoryEngineering
LocationSharjah
RemoteOn-site (inferred)
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted3 Jul 2026
Last verified30 Jul 2026
SourceEmployer career page (greenhouse)
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Description
Overview Are you passionate about applying data science and artificial intelligence 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-Sharjah, UAE, we are applying cutting-edge AI, deep learning, and LLM techniques to revolutionize geospatial analysis and derive insight from imagery data. Our team develops Deep Learning and LLM 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 Software Development Engineer in this role, you will develop foundation and task specific deep learning and LLM models for various modalities of GIS data including Satellite imagery. If you are passionate about AI applied to remote sensing and imagery and developing AI applications, this is the place to be! Responsibilities Develop tools, APIs and pretrained models for DL and LLM workflows for imagery Develop foundation models for computer vision, language, location and multimodal data Develop AI Agents / Assistants to perform various imagery tasks Author and maintain samples showcasing AI/LLM applications in various ArcGIS platforms Perform comparative studies of various AI architectures and their applications to solve complex problems using imagery Requirements 2+ years of experience with Python, in data science, deep learning, LLM Self-learner with extensive knowledge of machine learning, deep learning and LLM 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) Transformer models applied to computer vision and natural language processing Development of AI assistants / Agents to perform specific tasks Building from the scratch / finetuning, multi modal foundation models Bachelor's degree in computer science, engineering, or related disciplines from IITs and other top-tier engineering colleges Existing work authorization for UAE Recommended Qualifications Experience applying deep learning to satellite imagery or geospatial datasets Familiarity with ArcGIS suite of products and concepts of GIS Practical experience applying deep learning concepts from theory to code, evidenced by at least one significant project (internship, research, or personal portfolio) Experience building and orchestrating multi-agent systems with tools like LangGraph, paired with expertise in model fine-tuning, safety controls, and data-driven evaluation techniques to validate agent performance. #LI-PK1 #LI-Onsite The Company 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 life’s 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 Esri’s Racial Equity and Social Justice initiatives, please visit our website here . If you don’t meet all of the preferred qualifications for this position, we encourage you to still apply! Esri is an equal opportunity employer (EOE) and all qualified applicants will receive consider
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