. : AI/ML/GenAI Architect with Microsoft Azure Cloud skills
Responsibilities:
Design and implement advanced AI solutions, including machine learning models, computer vision applications, OCR systems, and Generative AI (GenAI) solutions using frameworks like TensorFlow, Pytorch, OpenCV and Langchain.
knowledge of AI orchestration, AI Agents, Agentic AI, Enterprise Integration skills, distributed and event based architectures
Develop end-to-end machine learning pipelines, from data collection and preprocessing to model training and deployment, utilizing Python libraries such as Pandas and NumPy.
Architect and implement robust MLOps infrastructure to support model training, monitoring, and deployment, leveraging Azure ML, Azure Document Intelligence, and Azure DevOps.
Lead AI/ML projects from conceptualization to production, focusing on the development and deployment of Large Language Models (LLMs) for various applications.
Conduct comprehensive data analysis, statistical validation, and model performance evaluation, employing SQL proficiency and ETL processes.
Implement CI/CD pipelines for seamless deployment and integration of AI models, using Git for version control and Databricks for collaborative data science workflows.
Skills:
Knowledge of Large Language Models (LLMs) and Generative AI (GenAI)
Machine Learning, Computer Vision, Image Processing, OCR
Proficient in Python, including libraries such as Pandas, NumPy, OpenCV, and TensorFlow
Experience with Azure SDK for Python and Flask-based REST APIs
SQL proficiency and experience with ETL processes
Azure Document Intelligence and model deployment in Azure
Familiarity with Git, Azure ML, and Azure DevOps
Experience with Databricks and MLflow
Work Experience
1
. : AI/ML/GenAI Architect with Microsoft Azure Cloud skills
Responsibilities:
Design and implement advanced AI solutions, including machine learning models, computer vision applications, OCR systems, and Generative AI (GenAI) solutions using frameworks like TensorFlow, Pytorch, OpenCV and Langchain.
knowledge of AI orchestration, AI Agents, Agentic AI, Enterprise Integration skills, distributed and event based architectures
Develop end-to-end machine learning pipelines, from data collection and preprocessing to model training and deployment, utilizing Python libraries such as Pandas and NumPy.
Architect and implement robust MLOps infrastructure to support model training, monitoring, and deployment, leveraging Azure ML, Azure Document Intelligence, and Azure DevOps.
Lead AI/ML projects from conceptualization to production, focusing on the development and deployment of Large Language Models (LLMs) for various applications.
Conduct comprehensive data analysis, statistical validation, and model performance evaluation, employing SQL proficiency and ETL processes.
Implement CI/CD pipelines for seamless deployment and integration of AI models, using Git for version control and Databricks for collaborative data science workflows.
Skills:
Knowledge of Large Language Models (LLMs) and Generative AI (GenAI)
Machine Learning, Computer Vision, Image Processing, OCR
Proficient in Python, including libraries such as Pandas, NumPy, OpenCV, and TensorFlow
Experience with Azure SDK for Python and Flask-based REST APIs
SQL proficiency and experience with ETL processes
Azure Document Intelligence and model deployment in Azure
Familiarity with Git, Azure ML, and Azure DevOps
* Experience with Databricks and MLflow
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