GenAI/AI/ML architect with Cloud
- Quest Global
- 10 - 15 years
- Bengaluru
- 4 months ago
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Job Description
Job Requirements1. 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
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
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Solution ArchitectEmployement Type: Full timeContact Details:
Company: Quest GlobalLocation(s): Bengaluru
Keyskills: continuous integration numpy artificial intelligence azure devops sql cloud tensorflow git devops pytorch etl azure identity architecture cd rest python microsoft azure machine learning pandas data bricks microsoft flow vision processing flask opencv etl process
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