Artificial Intelligence Software Developer

3 days ago

Aurangabad, Maharashtra, India beBeeSoftware Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

Transforming the World through Technology

We are seeking an experienced Software Engineer with a proven track record in designing, developing, and deploying AI/ML solutions at an enterprise level.

The ideal candidate will bring hands-on experience in Computer Vision, Deep Learning, Generative AI, and GIS-based AI applications, along with strong programming, analytical, and solution-building skills.

  • Must Have:
  • - 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:
  • - 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:
  • - 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.
  • This is a great opportunity to transform the world through technology.
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