Remote Senior MLOps Engineer - Azure, CI/CD & Governance

Promptcube3; United States; Teletrabalho; USD 120 000 - 180 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Competitive salary

Multinational environment

Comprehensive healthcare

Long-term B2B contract

Fully remote model

Resumo da oferta

Promptcube3 is seeking a Senior DevOps ML Engineer for a fully remote, long-term enterprise AI platform. The role centers on MLOps, DevOps infrastructure, and production-grade ML workloads, with emphasis on automation, governance, and security in regulated environments.

Responsibilities include building MLOps on Azure, optimizing ML pipelines, and implementing Terraform IaC, CI/CD, and ModelOps workflows. Collaboration with AI engineers and data teams is essential for reliability and compliance.

Qualificações

• Strong hands-on experience with Azure Databricks, including MLflow and Unity Catalog.
• Proven background in DevOps or MLOps for AI/ML platforms.
• Solid experience with Azure Cloud services and CI/CD automation.

Responsabilidades

• Design, build, and maintain MLOps and DevOps infrastructure on Azure.
• Develop and optimise ML pipelines for deployment, monitoring, and governance.
• Implement CI/CD pipelines and automated ModelOps workflows.
• Ensure data governance, lineage, and schema evolution.
• Apply Infrastructure as Code using Terraform.
• Collaborate with AI engineers and data teams to production ML systems.
• Monitor platform stability, performance, security, and compliance.
• Support operational readiness of ML workloads in regulated environments.

Conhecimentos

MLOps

DevOps

Automation

Azure cloud

Security/compliance mindset

Ferramentas

Azure Databricks

MLflow

Unity Catalog

Terraform

Docker

Kubernetes

Descrição da oferta de emprego

Promptcube3 is seeking a Senior DevOps ML Engineer for a fully remote, long-term enterprise AI platform. The role centers on MLOps, DevOps infrastructure, and production-grade ML workloads, with emphasis on automation, governance, and security in regulated environments.

Responsibilities include building MLOps on Azure, optimizing ML pipelines, and implementing Terraform IaC, CI/CD, and ModelOps workflows. Collaboration with AI engineers and data teams is essential for reliability and compliance.