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External Job Description
FADA is seeking an AI Developer to design and deploy AI and ML capabilities for geospatial intelligence across cloud and air‑gapped environments. The role includes developing deep learning models, fine‑tuning foundation models, building agentic AI systems, and supporting mission operations.
Responsibilities include creating models for object detection, segmentation, image translation, point cloud classification, time‑series forecasting, and vision transformers. The role involves fine‑tuning geospatial and general foundation models using methods such as LoRA and QLoRA, building LLM and VLM workflows, and developing agent systems for reasoning, planning, and tool use. Additional duties include generating geospatial embeddings, building knowledge graphs, developing NLP pipelines, evaluating architectures, and supporting AutoML.
The developer will build AI pipelines on Azure and deploy models using Docker, Kubernetes, Helm, vLLM, Triton, TorchServe, FastAPI, Ollama, and LocalAI. The role includes optimising models with ONNX, TensorRT, quantisation, and distillation, producing architecture documentation, and establishing MLOps practices such as versioning, tracking, retraining, and monitoring. Responsible AI practices, explainability, and compliance with defence requirements are essential.
Qualifications include a degree in a relevant field, 5 or more years of Python deep learning experience, and strong skills in PyTorch, TensorFlow, scikit‑learn, NumPy, and Pandas. Experience with foundation models, geospatial models, agentic AI frameworks, Azure deployment, offline model hosting, NLP tasks, and API development is required. Strong engineering practices are expected.
Preferred skills include RAG, vector databases, geospatial embeddings, knowledge graphs, open‑weight model deployment, RLHF or DPO, GeoAI, satellite imagery, responsible AI, GPU acceleration, distributed training, model optimisation, multisource geospatial data, GIS tools, and defence or national security experience.
FADA is seeking an AI Developer to design and deploy AI and ML capabilities for geospatial intelligence across cloud and air‑gapped environments. The role includes developing deep learning models, fine‑tuning foundation models, building agentic AI systems, and supporting mission operations.
Responsibilities include creating models for object detection, segmentation, image translation, point cloud classification, time‑series forecasting, and vision transformers. The role involves fine‑tuning geospatial and general foundation models using methods such as LoRA and QLoRA, building LLM and VLM workflows, and developing agent systems for reasoning, planning, and tool use. Additional duties include generating geospatial embeddings, building knowledge graphs, developing NLP pipelines, evaluating architectures, and supporting AutoML.
The developer will build AI pipelines on Azure and deploy models using Docker, Kubernetes, Helm, vLLM, Triton, TorchServe, FastAPI, Ollama, and LocalAI. The role includes optimising models with ONNX, TensorRT, quantisation, and distillation, producing architecture documentation, and establishing MLOps practices such as versioning, tracking, retraining, and monitoring. Responsible AI practices, explainability, and compliance with defence requirements are essential.
Qualifications include a degree in a relevant field, 5 or more years of Python deep learning experience, and strong skills in PyTorch, TensorFlow, scikit‑learn, NumPy, and Pandas. Experience with foundation models, geospatial models, agentic AI frameworks, Azure deployment, offline model hosting, NLP tasks, and API development is required. Strong engineering practices are expected.
Preferred skills include RAG, vector databases, geospatial embeddings, knowledge graphs, open‑weight model deployment, RLHF or DPO, GeoAI, satellite imagery, responsible AI, GPU acceleration, distributed training, model optimisation, multisource geospatial data, GIS tools, and defence or national security experience.
Key Skills
Ranked by relevance
ai
deep learning
cloud
kubernetes
tensorflow
fastapi
pytorch
python
docker
pandas
numpy
mlops
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- Posted
- Apr 08, 2026
- Type
- Full-time
- Level
- Not Applicable
- Location
- United Arab Emirates
- Company
- EDGE
Industries
Defense
Space Manufacturing
Categories
Engineering
Information Technology
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