Agentic Ai ML (NCS/Job/ 2473)
Job Skills
Job Description
Primary Responsibilities:
· AI/ML Development and Deployment:
o Architect and implement scalable ML solutions using Azure ML Studio and Azure Machine Learning services
o Fine-tune and deploy LLMs for enterprise-grade applications
o Design and build RAG pipelines leveraging Azure services and vector databases
o Develop and orchestrate multi-agent LLM systems for complex workflows
o Ensure robust model deployment, monitoring, and performance optimization in production environments
· Azure Platform Engineering:
o Leverage Azure services such as Azure Data Lake, Azure Synapse, Azure Blob Storage, and Azure Cognitive Search for data ingestion and processing
o Integrate AI models with Azure-based data pipelines and APIs
o Use Azure DevOps for CI/CD of ML workflows and model versioning
o Apply MLOps best practices for model governance, monitoring, and retraining
o Ensure compliance with data governance, privacy, and security standards in cloud environments
· Data Engineering and Processing:
o Build and maintain ETL/ELT pipelines for structured and unstructured data using Databricks and Apache Spark
o Prepare and transform structured and unstructured data using Python, PySpark, and SQL for training and inference
· Collaboration and Innovation:
o Collaborate with data scientists, product managers, and engineers to deliver AI-driven features
o Stay current with advancements in generative AI, LLMs, and Azure AI services
o Contribute to the continuous improvement of AI/ML pipelines and best practices
Required Qualifications:
· Experience:
o 5+ years of hands-on experience in AI/ML engineering with a focus on Azure
o Proven experience in deploying ML models using Azure ML Studio and Azure Machine Learning
o Experience working with LLMs, RAG systems, and AI agents
· Technical Skills:
o Experience with Databricks, Apache Spark, and Azure Data services
o Familiarity with MCP, Langchain, vector databases and embedding models
o Knowledge of Azure DevOps and CI/CD for ML workflows
o Proficiency in Python, SQL, LLMs and PySpark
· Soft Skills:
o Proven solid analytical and problem-solving skills
o Proven effective communication and collaboration with cross-functional teams
o Demonstrated ability to translate business requirements into technical solutions
