
Senior AI/ML Solutions Architect
2 days ago
We are seeking a highly skilled Software Engineer with extensive expertise in designing, developing, and deploying cutting-edge AI/ML solutions at an enterprise level. The ideal candidate will possess hands-on experience in Computer Vision, Deep Learning, Generative AI, and GIS-based AI applications, along with strong programming, analytical, and solution-building skills.
Key Responsibilities:- Design, develop, and deploy AI/ML solutions that drive business growth and innovation
- Contribute to the development of AI-powered GIS platforms, multimodal and geospatially aware models, and real-time feature detection systems
- Collaborate with cross-functional teams to translate research into applied enterprise use cases
- 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
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