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Software Development Engineer II

Esri
, UAE
Internship
Mid
Onsite
PythonDeep LearningMachine LearningComputer VisionLarge Language ModelsPyTorch
Free

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PythonDeep LearningMachine Learning
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Overview

  • Esri is the world leader in geographic information systems (GIS) and developer of ArcGIS.
  • 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.
  • As a Software Development Engineer, you will develop foundation and task specific deep learning and LLM models for various modalities of GIS data including Satellite imagery.

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; Transformer models applied to computer vision and NLP; Development of AI assistants / Agents; Building from 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.
  • 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.

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