Acuity Analytics
Senior DevOps/MLOps Engineer (Azure, Python) F/M/X
Software Engineering - Ref: 26554, Austria, Graz, United Kingdom - Full Time
Ascent has recently been acquired by Acuity Analytics. This is both a significant milestone for us and a tremendous opportunity for you. Acuity Analytics is a business with a strong global reputation, an impressive client base and ambitious growth plans. We deliver deep insights and domain-led digital transformation to high-growth and heavily regulated organizations. To our customers, we bring a partnership that provides the talent, technology and capability to enhance performance and operational efficiency.
About the role
We are hiring a senior hands-on MLOps Engineer who blends strong DevOps fundamentals with machine learning delivery. You will build and run the CI/CD pipelines that move ML and application artifacts safely across environments on Azure, and keep those services reliable in production.
Key responsibilities
Design, build and maintain CI/CD pipelines for ML models, data components and supporting services
Create pipelines that promote artifacts (models, packages, containers, configuration) across environments, such as dev, test, staging and production, with the right gates and approvals
Integrate pipelines with Azure services, for example Azure DevOps or GitHub Actions, Azure Machine Learning, container registries, Key Vault and storage
Write and maintain Python scripts and tooling that automate pipeline steps, deployments and operational tasks
Implement and manage authentication and authorization for pipelines, including service principals, managed identities, secrets handling and least-privilege access
Run and support services in production: monitoring, alerting, incident response, troubleshooting and continuous improvement
Work with data scientists, ML engineers and platform teams to turn experimental work into repeatable, production-ready delivery
Document pipelines and operating procedures so other teams can use and support them
Required qualifications
Proven experience with CI/CD processes and tooling in a production setting
Experience designing pipelines that promote artifacts across multiple environments
Hands-on experience integrating with Azure services
Strong Python skills, including scripting and automation
Experience building authentication mechanisms for pipelines (service principals, managed identities, token-based access, secrets management)
Experience running services in production and supporting them operationally
Working knowledge of MLOps concepts: model packaging, versioning, deployment and monitoring
Solid understanding of version control, infrastructure as code and containerization
Clear communication and the ability to collaborate with data science and engineering teams
Nice to have
Hands-on experience with GitHub Copilot in day-to-day engineering work
Exposure to AI adoption strategies in an enterprise environment, such as rollout, enablement, governance and measuring impact
Experience with Azure Machine Learning or comparable MLOps platforms
Familiarity with monitoring and observability for ML workloads
Why join us
People are at the Heart of our Business. By investing in people, we achieve exceptional results for our clients and create new opportunities for our teams to thrive. Check out this page for more details.
If you have any questions contact our Talent Acquisition team on ta.admin@acuityanalytics.
For more details about Acuity Analytics please see here: Read here.
