Azure MLOps Architect / Consultant

Resource 1 is in need of an Azure ML Architect / Consultant on a contract, remote basis for approximately 1-3 months (can be part-time or full-time hours). This is a high-level advisory/consultative position. The consultant will assess current predictive modeling workflows and design an Azure-based ML architecture to streamline model scoring, deployment, and integration with Salesforce. They will deliver best practices, documentation, training, and cost/monitoring guidance to enable the internal team to operate and scale models and pipelines. The engagement may include a proof-of-concept migration of one model and recommendations for hosting self-service web apps and optional LLM usage guidance.

Responsibilities:

·         Assess existing predictive models, local workflows, and data sources and document architectural requirements.

·         Recommend Azure ML architecture and specific Azure services required based on best practices.

·         Provide guidance and documentation for deployment, monitoring, and cost forecasting of Azure ML workloads.

·         Advise on data pipeline design from Oracle to Azure and patterns to integrate scored outputs into Salesforce.

·         Deliver training, demos, and knowledge transfer to internal team members and produce runbooks.

·         Develop a plan and assist with configuration/setup of the Azure environment and subscription considerations.

·         Support a proof-of-concept migration of one model to Azure as a template for future models.

·         Advise on hosting options for custom self-service web apps and containerization strategies.

Required Skills & Experience:

·         Proven experience designing and deploying Azure ML solutions and ML operationalization.

·         Deep knowledge of Azure services (Azure ML, Data Factory or Pipelines, compute and storage) and cost drivers.

·         Experience building or advising on data pipelines from Oracle or similar data warehouses into cloud environments.

·         Familiarity with integrating ML outputs into Salesforce (including MuleSoft or other integration patterns).

·         Strong ability to produce documentation, runbooks, training materials, and conduct knowledge transfer.

·         Expertise in monitoring, governance, security, and permissions for Azure ML workloads.

Plusses:

·         Experience with Azure OpenAI / LLM integrations and governance for AI usage.

·         Hands-on experience hosting web applications on Azure (AKS, containers, App Service) for self-service tools.

·         Prior experience in higher education or nonprofit analytics environments.

Medical insurance and a 401(k) plan is offered to all eligible W2 employees.