GenAI/AI/ML architect with Cloud

Job Requirements

1. Job Description : 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. Job Description : 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