AI Machine Learning Engineer

Applicants must be legally authorized to work in the United States. This position is not eligible for visa sponsorship now or in the future.
This role requires residency in South Florida. Candidates located outside this area will not be considered. Relocation, if applicable, is at the candidate’s own expense.
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.