Pay: Salary not listed in the saved posting
Work setup: Remote stated — work setup source
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.
Read the full posting
Employment: Unconfirmed

What you’ll work on

Design, build, and maintain MLOps and DevOps infrastructure on Azure
Collaborate closely with AI engineers and data teams to support production ML systems
Develop and optimise ML pipelines for deployment, monitoring, and governance

From the employer’s posting

Responsibilities Design, build, and maintain MLOps and DevOps infrastructure on Azure Develop and optimise ML pipelines for deployment, monitoring, and governance

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

Design, build, and maintain MLOps and DevOps infrastructure on Azure Develop and optimise ML pipelines for deployment, monitoring, and governance Work with Azure Databricks, MLflow, and Unity Catalog

What you’ll bring

All qualifications

Core experience

Solid experience with Azure Cloud services
Strong understanding of data governance, access control, and compliance principles
Python development or scripting experience
Experience working in insurance or other regulated environments

Qualification wording

Solid experience with Azure Cloud services

Strong understanding of data governance, access control, and compliance principles

Python development or scripting experience

Experience working in insurance or other regulated environments

Tools in this posting

Azure
Kubernetes
Python
Databricks
Docker
Terraform
MLflow

Source

Responsibilities - Design, build, and maintain MLOps and DevOps infrastructure on Azure - Develop and optimise ML pipelines for deployment, monitoring, and governance

- Develop and optimise ML pipelines for deployment, monitoring, and governance - Work with Azure Databricks, MLflow, and Unity Catalog - Implement CI/CD pipelines and automated ModelOps workflows

Requirements - Strong hands-on experience with Azure Databricks, including MLflow and Unity Catalog - Proven background in DevOps or MLOps for AI / ML platforms

- Proven background in DevOps or MLOps for AI / ML platforms - Solid experience with Azure Cloud services - Hands-on CI/CD and pipeline automation experience

- Python development or scripting experience - Docker and Kubernetes knowledge - Exposure to Generative AI or broader ML workflows

Nice to have - Python development or scripting experience - Docker and Kubernetes knowledge

- 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

- Hands-on CI/CD and pipeline automation experience - Infrastructure as Code expertise using Terraform - Strong understanding of data governance, access control, and compliance principles

Benefits in the posting

Full benefits wording

Comprehensive healthcare
Fully remote model

From the employer’s posting.

Job description

View original posting ↗

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 maintain MLOps and DevOps infrastructure on Azure
Develop and optimise ML pipelines for deployment, monitoring, and governance
Work with Azure Databricks, MLflow, and Unity Catalog
Implement CI/CD pipelines and automated ModelOps workflows
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

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
Hands-on CI/CD and pipeline automation experience
Infrastructure as Code expertise using Terraform
Strong understanding of data governance, access control, and compliance principles
Confident English for daily cooperation with international stakeholders

Nice to have

Python development or scripting experience
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

Your next step

Have your CV and examples of relevant work ready.
Check the listed location, eligibility and core experience before starting.
Ask the employer about the salary range before committing time to the process.

Complete your application on madiffpl.zohorecruit.com. The employer’s form will show what is required.

Already applied? Track this application

Source & posting history

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay: No pay amount identified in the saved description.
Location & working pattern: Location not supplied.
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.
More source context
- Long-term B2B contract with stable project pipeline - Fully remote model
Work authorization: No clear work-authorization passage found. Eligibility is unconfirmed.

Open source at madiffpl.zohorecruit.com ↗Read the full description ↓

Status in our records: Active
First seen by us: Jun 3, 2026
Recorded sightings: 162
Last seen by us: Oct 9, 2026

These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.

Report an error

See how this role fits your experience

Add your resume to compare the role’s scope, tools and requirements with your experience.

Upload resume Add LinkedIn