ML Architect
Job Description:
Pay Range: $60hr - $65hr
Key Skills:
Experience with Azure Machine Learning, Azure OpenAI, Azure DevOps, and AKS.
Document architecture, workflows, and best practices for knowledge sharing and compliance.
Provide technical oversight & Guidelines.
Architect and implement end-to-end MLOps and LLMOps pipelines using Azure Machine Learning and Azure OpenAI.
Design scalable infrastructure for training, deploying, and monitoring ML and LLM models in production.
Collaborate with data scientists and engineers to streamline model development, testing, and deployment workflows.
Manage Azure Kubernetes Service (AKS) clusters and containerized ML workloads.
Ensure model governance, versioning, and reproducibility using tools like MLflow and Azure DevOps.
Promote DevSecOps practices, ensuring security and compliance are embedded in the ML lifecycle.
Monitor and troubleshoot production ML systems, ensuring high availability and performance.
Proficiency in Python, Docker, Kubernetes, and CI/CD pipelines.
Experience with LLM fine-tuning, prompt engineering, and model deployment.
Familiarity with MLflow, Terraform, and monitoring tools like PrometheGrafana.
Employers have access to artificial intelligence language tools (AI) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
Report this job
Dice Id:
10516350
Position Id:
2025-220577
Job Description:
Pay Range: $60hr - $65hr
Key Skills:
Experience with Azure Machine Learning, Azure OpenAI, Azure DevOps, and AKS.
Document architecture, workflows, and best practices for knowledge sharing and compliance.
Provide technical oversight & Guidelines.
Architect and implement end-to-end MLOps and LLMOps pipelines using Azure Machine Learning and Azure OpenAI.
Design scalable infrastructure for training, deploying, and monitoring ML and LLM models in production.
Collaborate with data scientists and engineers to streamline model development, testing, and deployment workflows.
Manage Azure Kubernetes Service (AKS) clusters and containerized ML workloads.
Ensure model governance, versioning, and reproducibility using tools like MLflow and Azure DevOps.
Promote DevSecOps practices, ensuring security and compliance are embedded in the ML lifecycle.
Monitor and troubleshoot production ML systems, ensuring high availability and performance.
Proficiency in Python, Docker, Kubernetes, and CI/CD pipelines.
Experience with LLM fine-tuning, prompt engineering, and model deployment.
Familiarity with MLflow, Terraform, and monitoring tools like PrometheGrafana.
Employers have access to artificial intelligence language tools (AI) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
Report this job
Dice Id:
10516350
Position Id:
2025-220577
Job ID: 482838709
Originally Posted on: 6/26/2025
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