AI/ML Engineer - Azure C# (28558)

Role overview

• check_circle Architect and implement AI/ML solutions using Azure Machine Learning, Azure AI Foundry, Cognitive Services, and Azure OpenAI.
• check_circle Build and deploy NLP and LLM-based models using frameworks such as LangChain, Semantic Kernel, or LlamaIndex.
• check_circle Design and implement Retrieval-Augmented Generation (RAG) pipelines using Azure AI Search.
• check_circle Develop and manage RESTful API endpoints using C# (.NET) and Python (FastAPI).
• check_circle Implement CI/CD pipelines and MLOps workflows using Azure DevOps and GitHub.
• check_circle Use Terraform for infrastructure-as-code (IaC) to provision and manage Azure cloud resources.
• check_circle Lead end-to-end ML model lifecycle including data exploration, feature engineering, model training, validation, and deployment.
• check_circle Monitor and maintain deployed models in production environments.
• check_circle Conduct thorough testing and validation of AI models to ensure accuracy, reliability, and fairness.
• check_circle Collaborate with cross-functional teams including product owners and end users to ensure solutions meet business needs.
• check_circle Contribute to client-facing engagements, including solution design, proposal development, and technical presentations.
• check_circle 3+ years of experience in AI/ML development, with a focus on OpenAI Services, NLP, and LLMs.
• check_circle Proven experience with end-to-end deployment, monitoring, and maintenance of ML models on Azure (preferred) or AWS.
• check_circle Hands-on experience with Azure AI Foundry and Azure Machine Learning.
• check_circle Strong background in applied data science, including model selection, validation, and optimization.
• check_circle Proficiency in Python and C#.
• check_circle Experience developing and managing APIs using FastAPI or .NET.
• check_circle Familiarity with MLOps practices and tools such as Azure DevOps, GitHub Actions, and Terraform.
• check_circle Strong communication skills and ability to work with both technical and non-technical stakeholders.
• check_circle Self-directed learner with a proactive approach to problem-solving.

Preferred qualifications

• Experience in a consulting or client-facing role, delivering tailored AI solutions.
• Familiarity with RAG architectures and tools like LangChain, Semantic Kernel, or LlamaIndex.
• Knowledge of data pipeline development using Azure Data Factory or similar tools.
• Experience contributing to proposals, estimates, and solution architecture in a pre-sales context.

Benefits