Advanced Geospatial AI Specialist

2 days ago

Ghaziabad, Uttar Pradesh, India beBeeMachineLearning Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Senior AI Engineer

We are seeking an experienced Senior AI Engineer to join our team. The ideal candidate will bring expertise in designing, developing, and deploying AI/ML solutions at an enterprise level.

  • Must-Have Skills:
    • 3–5 years of hands-on experience in implementing AI/ML solutions in enterprise or large-scale production environments.
    • Strong programming proficiency in Python with practical use of TensorFlow, PyTorch, Keras, scikit-learn, NumPy, Pandas, and OpenCV.
    • Proven experience with Computer Vision architectures, including YOLO, SAM, U-Net, and other CNN-based models for real-time object detection, segmentation, and feature extraction.
    • Expertise in image classification using advanced CV models (e.g., ResNet, VGG, YOLOv5/v8, EfficientNet).
    • Deep understanding and implementation experience of machine learning algorithms (supervised, unsupervised, and reinforcement learning) for classification, regression, and clustering.
    • Experience in Generative AI and Large Language Models (LLMs), including transformers, diffusion models, multimodal pipelines, and speech-to-text/NLP solutions.
    • Strong foundation in mathematics, statistics, data structures, algorithms, and optimization techniques.
    • Hands-on experience with RNNs/LSTMs, hybrid neural architectures, and temporal/spatiotemporal modeling.
    • Practical knowledge of Agentic AI systems (AI agents, multi-agent workflows, or autonomous agent design).
    • GIS domain expertise – demonstrated ability to integrate AI/ML with geospatial datasets, satellite imagery, and spatial analytics to deliver practical solutions.
    • End-to-end experience in AI/ML solution lifecycle – from data preprocessing, model training, evaluation, deployment, and scaling.
    • Hands-on exposure to geospatial toolkits/libraries (e.g., GDAL, GeoPandas, QGIS, ArcGIS APIs) and their integration with ML workflows.
  • Should-Have Skills:
    • Working knowledge of MLOps/LLMOps workflows for scalable, automated AI/ML deployments (CI/CD, containerization, orchestration).
    • Experience with enterprise-grade data platforms (cloud-native, distributed systems) ensuring high performance and interoperability with AI workloads.
    • Practical exposure to geospatial feature extraction, change detection, and segmentation workflows.
    • Strong ability to communicate AI/GIS solutions, collaborate with cross-functional teams, and translate research into applied enterprise use cases.
  • Could-Have Skills:
    • Certifications in AI/ML, GIS, or cloud platforms (AWS, Azure, GCP).
    • Familiarity with scientific computing libraries (SciPy, Theano, Julia ecosystem).
    • Experience contributing to AI/GIS research publications, open-source projects, or innovation programs.
    • Knowledge of emerging paradigms such as federated learning, multi-agent systems, spatial AI, or Responsible AI practices.

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