Software Development Engineer II
On-siteSharjah, Sharjah, United Arab Emirates
Job Summary
Develop foundation and task-specific deep learning and LLM models for satellite imagery and GIS data, including computer vision, language, and multimodal modalities. Build AI agents and assistants to perform specific imagery tasks, author samples showcasing applications in ArcGIS platforms, and conduct comparative studies of AI architectures. Develop tools, APIs, and pretrained models for DL and LLM workflows while fine-tuning or building multi-modal foundation models from scratch. Requires 2+ years of Python experience in data science and deep learning, with expertise in transformer models and multi-agent systems. Located onsite at Esri R&D Center-Sharjah, UAE.
Required Qualifications
- 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
Desired 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
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