Senior DevOps ML Engineer

Promptcube3; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive salary

Multinational environment

Comprehensive healthcare

Long-term B2B contract

Fully remote model

Job summary

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.

Qualifications

• 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.

Responsibilities

• 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.

Skills

MLOps

DevOps

Automation

Azure cloud

Security/compliance mindset

Tools

Azure Databricks

MLflow

Unity Catalog

Terraform

Docker

Kubernetes

Job description

This is a remote position. We are looking for a Senior DevOps ML Engineer to support a long-term enterprise AI platform focused on production-grade ML workloads. This role is fully centred on MLOps and DevOps infrastructure — ensuring that existing AI and ML models run reliably, securely, and at scale in production. The position operates in a regulated environment and requires strong focus on automation, governance, and operational excellence.

Responsibilities Design, build, and maintainMLOpsand DevOps infrastructure on Azure Develop andoptimiseML pipelines for deployment, monitoring, and governance Work with Azure Databricks,MLflow, and Unity Catalog Implement CI/CD pipelines and automatedModelOpsworkflows Ensure data architecture supports governance, lineage, and schema evolution Apply Infrastructure as Code using Terraform Collaborate closely with AI engineers and data teams to support production ML systems Monitor and ensure platform stability, performance, security, and compliance Support operational readiness of ML workloads in regulated environments

Requirements Stronghands-onexperiencewithAzureDatabricks,includingMLflowand UnityCatalog Proven background in DevOps orMLOpsfor AI / ML platforms Solid experience with Azure Cloud services Hands-on CI/CD and pipeline automation experience Infrastructure as Codeexpertiseusing Terraform Strong understanding of data governance, access control, and compliance principles Confident English for daily cooperation with international stakeholders Nice to have Pythondevelopmentorscriptingexperience Docker and Kubernetes knowledge Exposure to Generative AI or broader ML workflows Experience working in insurance or other regulated environments

Benefits Solid, competitive salary Work in multinational environment on international projects Comprehensive healthcare Long-term B2B contract with stable project pipeline Fully remote model Originally posted on Himalayas