Software Architect

1 week ago

Nashik, Maharashtra, India beBeeMachineLearning Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

Job Opening – Software Professional

We are seeking a skilled software professional with expertise in designing, developing, and deploying AI/ML solutions at an enterprise level. The ideal candidate will have hands-on experience in computer vision, deep learning, generative AI, and GIS-based AI applications.

Must Have Skills:

  • 3–5 years of proven expertise 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.

Desirable Skills:

  • MLOps/LLMOps workflows for scalable, automated AI/ML deployments (CI/CD, containerization, orchestration).
  • 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.

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