Trust IT LLC
Dallas, Texas
Job Description • Architect and integrate hybrid Al systems using Azure Machine Learning, Cognitive Services, and OpenAl, combining traditional ML, deep learning, target language models (LLMs), and retrieval-augmented generation (RAG) pipelines. • Design and deploy scalable Al architectures on Azure, including APis, microservices, and model-serving frameworks, ensuring seamless integration with analytics, simutation, and operational systems. • Lead the full Al/ML lifecycle on Azure-including data ingestion (Azure Data Factory, Azure Synapse), feature engineering, training, deployment, and ongoing sustainment within secure cloud environments (such as Azure Government and IL5/IL6 compliance). • Engineer event-driven data pipelines and feature stores for structured and unstructured data (text, imagery, simulation outputs) leveraging Azure Data Lake, Event Hubs, and Databricks. • Ensure Responsible Al practices by embedding traceability, explainability, and confidence scoring using Azure Responsible Al toolkits and frameworks. • Understanding of MLOps pipelines with Azure Machine Learning, MLflow, and Azure Kubernetes Service (AKS) to support CI/CD, retraining, and drift detection. • Transition R&D prototypes to production on Azure, optimizing deployments for constraints such as limited compute, edge environments (Azure loT Edge), or disconnected operations. • Provide technical leadership and mentorship, establishing standards for model quality, architecture, and ethical Al deployment across Azure-based programs. • Collaborate across engineering, data, and modeling teams to unify Al solutions, ensuring interoperability and reuse within Azure's ecosystem. • Support proposal and solution development by providing technical expertise in Azure Al/ML architectures, data strategies, and Responsible Al assurance frameworks.
Job Description • Architect and integrate hybrid Al systems using Azure Machine Learning, Cognitive Services, and OpenAl, combining traditional ML, deep learning, target language models (LLMs), and retrieval-augmented generation (RAG) pipelines. • Design and deploy scalable Al architectures on Azure, including APis, microservices, and model-serving frameworks, ensuring seamless integration with analytics, simutation, and operational systems. • Lead the full Al/ML lifecycle on Azure-including data ingestion (Azure Data Factory, Azure Synapse), feature engineering, training, deployment, and ongoing sustainment within secure cloud environments (such as Azure Government and IL5/IL6 compliance). • Engineer event-driven data pipelines and feature stores for structured and unstructured data (text, imagery, simulation outputs) leveraging Azure Data Lake, Event Hubs, and Databricks. • Ensure Responsible Al practices by embedding traceability, explainability, and confidence scoring using Azure Responsible Al toolkits and frameworks. • Understanding of MLOps pipelines with Azure Machine Learning, MLflow, and Azure Kubernetes Service (AKS) to support CI/CD, retraining, and drift detection. • Transition R&D prototypes to production on Azure, optimizing deployments for constraints such as limited compute, edge environments (Azure loT Edge), or disconnected operations. • Provide technical leadership and mentorship, establishing standards for model quality, architecture, and ethical Al deployment across Azure-based programs. • Collaborate across engineering, data, and modeling teams to unify Al solutions, ensuring interoperability and reuse within Azure's ecosystem. • Support proposal and solution development by providing technical expertise in Azure Al/ML architectures, data strategies, and Responsible Al assurance frameworks.