VSE Aviation ยท 3 hours ago
AI Machine Learning Engineer
VSE Aviation is seeking an AI Machine Learning Engineer to help build, deploy, and operationalize AI solutions within their Microsoft-based technology ecosystem. The role involves developing machine learning models, integrating AI into enterprise applications, and collaborating with various stakeholders to translate use cases into workable solution designs.
AerospaceIndustrialManufacturing
Responsibilities
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
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
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
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
Qualification
Required
Hands-on experience developing machine learning models
Integrating AI capabilities into enterprise applications
Leveraging Microsoft Azure's AI and data services
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
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
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
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