We are seeking a skilled AI Engineer with strong hands-on experience in Azure AI and Machine Learning services. The ideal candidate will design develop and deploy scalable AI/ML and Generative AI solutions leveraging Azure Cloud technologies Microsoft Fabric and Azure AI Foundry to solve complex business challenges and drive innovation
Key Responsibilities
- Design develop and deploy AI/ML models using Azure Machine Learning Azure Databricks and Microsoft Fabric.
- Build and operationalize LLM-based solutions leveraging Azure AI Foundry Azure OpenAI and Cognitive Services.
- Implement RAG-based architectures using Azure AI Search Vector Databases and LangChain or LangGraph frameworks.
- Collaborate with Data Engineers and Architects to integrate AI applications with Microsoft Fabric datasets ensuring governance data lineage and reliability.
- Implement MLOps and LLMOps best practices for continuous integration delivery and monitoring of AI models using Azure ML Pipelines and Azure DevOps.
- Optimize model performance and ensure scalability security and reliability of deployed solutions.
- Work closely with business and technical stakeholders to translate requirements into AI-driven solutions.
- Stay up to date with emerging trends in AI GenAI and cloud-based ML technologies.
Qualifications :
- 58 years of experience in building and deploying AI/ML or GenAI solutions in production environments.
- Strong expertise in Azure Machine Learning Azure Databricks Microsoft Fabric Azure AI Foundry and Azure Cognitive Services.
- Proficiency in Python and major ML frameworks (PyTorch TensorFlow Scikit-learn).
- Hands-on experience with RAG architecture prompt engineering and LLM-based application development.
- Experience with MLOps/LLMOps pipelines model tracking and CI/CD using Azure DevOps.
- Familiarity with data integration across Microsoft Fabric Azure Data Factory or Synapse.
- Strong understanding of model lifecycle management monitoring and performance optimization using MLflow App Insights and Azure Monitor.
- Excellent problem-solving debugging and collaboration skills.
Remote Work :
No
Employment Type :
Full-time
We are seeking a skilled AI Engineer with strong hands-on experience in Azure AI and Machine Learning services. The ideal candidate will design develop and deploy scalable AI/ML and Generative AI solutions leveraging Azure Cloud technologies Microsoft Fabric and Azure AI Foundry to solve complex bus...
We are seeking a skilled AI Engineer with strong hands-on experience in Azure AI and Machine Learning services. The ideal candidate will design develop and deploy scalable AI/ML and Generative AI solutions leveraging Azure Cloud technologies Microsoft Fabric and Azure AI Foundry to solve complex business challenges and drive innovation
Key Responsibilities
- Design develop and deploy AI/ML models using Azure Machine Learning Azure Databricks and Microsoft Fabric.
- Build and operationalize LLM-based solutions leveraging Azure AI Foundry Azure OpenAI and Cognitive Services.
- Implement RAG-based architectures using Azure AI Search Vector Databases and LangChain or LangGraph frameworks.
- Collaborate with Data Engineers and Architects to integrate AI applications with Microsoft Fabric datasets ensuring governance data lineage and reliability.
- Implement MLOps and LLMOps best practices for continuous integration delivery and monitoring of AI models using Azure ML Pipelines and Azure DevOps.
- Optimize model performance and ensure scalability security and reliability of deployed solutions.
- Work closely with business and technical stakeholders to translate requirements into AI-driven solutions.
- Stay up to date with emerging trends in AI GenAI and cloud-based ML technologies.
Qualifications :
- 58 years of experience in building and deploying AI/ML or GenAI solutions in production environments.
- Strong expertise in Azure Machine Learning Azure Databricks Microsoft Fabric Azure AI Foundry and Azure Cognitive Services.
- Proficiency in Python and major ML frameworks (PyTorch TensorFlow Scikit-learn).
- Hands-on experience with RAG architecture prompt engineering and LLM-based application development.
- Experience with MLOps/LLMOps pipelines model tracking and CI/CD using Azure DevOps.
- Familiarity with data integration across Microsoft Fabric Azure Data Factory or Synapse.
- Strong understanding of model lifecycle management monitoring and performance optimization using MLflow App Insights and Azure Monitor.
- Excellent problem-solving debugging and collaboration skills.
Remote Work :
No
Employment Type :
Full-time
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