AI Machine Learning Engineer

SUMMARY: The AI Machine Learning Engineer will help build, deploy, and operationalize AI solutions within our Microsoft-based technology ecosystem. The ideal candidate has hands-on experience developing machine learning models, integrating AI capabilities into enterprise applications, leveraging Microsoft Azure’s AI and data services. This role will work closely with VP Corporate IT, cyber security, engineering, development, and business stakeholders to translate use cases into workable solution designs, developing, and optimizing models and pipelines that scale across the organization.

DUTIES & RESPONSIBILITIES:

Responsibilities include, but are not limited to:

AI/ML Solution Development:

• Design, build, and deploy ML models using Azure Machine Learning, Azure OpenAI, and other Microsoft AI services.
• Develop data preprocessing, feature engineering, model training, and evaluation pipelines.
• Implement prompt engineering, fine-tuning, and model orchestration for LLM-driven applications.

Azure Cloud Engineering:

• Use Azure Machine Learning, Copilot, Data Warehouse, Azure Databricks, Azure Synapse, and related services to build and manage ML workflows.
• Create scalable model endpoints and integrate them into internal or customer-facing applications.
• Optimize model performance and cost efficiency within Azure.

ML Operations & Deployment:

• Build and maintain CI/CD pipelines for ML models using Azure DevOps or GitHub Actions.
• Monitor deployed models, retrain as needed, and ensure production reliability.
• Implement logging, telemetry, and monitoring using Azure Monitor and related tools.

Collaboration & Strategy:

• Partner with the AI Initiative Lead to define solution architecture, constraints, and success metrics.
• Work with cross-functional teams to identify new AI opportunities and evaluate feasibility.
• Create documentation, model cards, and technical guides for internal teams.
• Other duties as assigned.

MINIMUM REQUIREMENTS:

• Bachelor’s degree in computer science or related field

+ or a combination of relevant Specialized Technical Certifications in related field.

+ or an additional 3 years of relevant work experience in lieu of degree.

• 5 years of experience building and deploying AI/ML models in production environments.
• Hands-on experience with Microsoft technologies, including:

+ Azure Machine Learning (pipelines, workspaces, endpoints)

+ Azure OpenAI Service

+ Azure Cognitive Services

+ Data Warehouse / Azure Data Lake / Synapse / Databricks

+ Azure DevOps or GitHub Actions

• Proficiency in Python, R and common ML frameworks (Microsoft Azure Machine Learning, TensorFlow, scikit-learn).

PREFERRED REQUIREMENTS:

• Strong knowledge of data engineering fundamentals, feature engineering, and model evaluation.
• Experience building APIs using FastAPI, Flask, or Azure Functions.
• Understanding of best practices for security, governance, and responsible AI (Microsoft Responsible AI Framework a plus).
• Experience with LLM application design (RAG patterns, vector databases, prompt engineering).
• Experience with Copilot, Azure AI Search, Azure Cognitive Search, Azure Cosmos DB, or Redis Enterprise for retrieval systems.
• Experience deploying containerized applications using Azure Kubernetes Service (AKS).
• Familiarity with enterprise integrations (Power Platform, Microsoft Graph).
• Experience supporting end-to-end AI product lifecycle in a corporate environment.

OTHER:

• The selected applicant will be subject to a background check and drug testing.