
GenAI/AI/ML architect with Cloud
2 days ago
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
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