Role Principal Consultant (ML Engineer) Technology Gen AI LLMs Azure Location UK Business Unit DNA Analytics Compensation Competitive (including bonus)
Job Description Principal Consultant to design develop and deploy solutions using GenAI LLMs and ML models utilizing Azure OpenAI services and other features of the Azure AI/ML landscape.
Your role We are looking for a skilled Principal Consultant with expertise in Azure to operationalize AI ML and Large Language Model (LLM) solutions at scale and will be responsible for designing implementing and maintaining the end-to-end Machine Learning pipelines and infrastructure that enable the seamless development deployment and monitoring of AI and ML models in production including Large Language Models (LLMs). from data ingestion and model/LLM deployment monitoring and governance using Azures AI ecosystem including Azure AI Foundry Azure ML and AKS.
Responsibilities
Design build and manage ML & LLM pipelines using Azure Machine Learning (AML) and Azure AI Foundry (e.g. GPT Phi LLaMA-based HuggingFace) using Azure AI services.
Implement and manage Azure infrastructure necessary for ML workloads (e.g. Azure Machine Learning Workspaces Compute Data Stores) using ARM templates or Terraform.
Implement CI/CD for ML/LLM workflows with Azure DevOps or GitHub Actions.
Manage real-time and batch deployments on Azure Kubernetes Service (AKS) or Azure Container Instances and manage model versions registrations and lifecycle within Azure Machine Learning. This includes working with Azure AI Foundry for generative AI applications.
Automate infrastructure with Terraform Bicep or ARM templates.
Set up model registry experiment tracking versioning and reproducibility.
Integrate Azure Data Factory Synapse or Databricks for data ingestion and preprocessing.
Establish robust monitoring logging and alerting systems for deployed ML models and LLMs to track performance detect data drift concept drift and operational issues ensuring continuous model health.
Ensure security compliance and responsible AI practices in LLM deployments.
Collaborate with cross-functional teams to operationalize AI/ML/LLM use cases at enterprise scale.
10 years of experience in ML engineering with hands-on experience in Azure AI/ML services.
Prior experience in LLM deployment or generative AI projects is strongly preferred.
Preferred
Strong programming experience in Python (ML frameworks Azure SDKs).
Hands-on experience with Azure ML Azure AI Foundry Azure OpenAI AKS Databricks ADF Synapse Azure Storage.
Experience deploying and monitoring LLMs in production (fine-tuning prompt engineering integration inference optimization).
Knowledge of CI/CD for ML/LLMs with Azure DevOps / GitHub Actions.
Proficiency with Docker and containerized deployments.
Familiarity with MLOps best practices version control reproducibility monitoring.
Good understanding of Responsible AI model governance and compliance frameworks.
Solid SQL and data pipeline skills.
Strong problem-solving and collaboration skills.
Nice-to-Have Skills:
Experience with LangChain Semantic Kernel or Retrieval-Augmented Generation (RAG) patterns in Azure.
Knowledge of vector databases (Azure Cognitive Search Pinecone Weaviate etc.) for LLM applications.
Exposure to real-time streaming & event-driven architectures (Event Hub Kafka).
Familiarity with KubeFlow MLflow or other MLOps orchestration frameworks.
Personal
Besides the professional qualifications of the candidates we place great importance in addition to various forms personality profile. These include:
High analytical skills
High customer orientation
High quality awareness
Excellent verbal and written communication skills
About Us Infosys is a global leader in next-generation digital services and consulting. We enable clients in more than 50 countries to navigate their digital transformation. With over four decades of experience in managing the systems and workings of global enterprises we expertly steer our clients through their digital journey. We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills expertise and ideas from our innovation ecosystem.
All aspects of employment at Infosys are based on merit competence and performance. We are committed to embracing diversity and creating an inclusive environment for all employees. Infosys is proud to be an equal opportunity employer.
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