Mlops Engineer

MLOps Engineer

We are seeking a highly motivated and skilled MLOps Engineer to support the design, automation, and operationalization of AI-driven cloud solutions. The ideal candidate will have deep hands-on expertise in Azure Cloud, Azure Databricks, Azure Machine Learning, and Azure AI Foundry, with strong focus on machine learning operations, infrastructure automation, and secure CI/CD pipeline management. This role ensures that AI and ML models are efficiently built, deployed, monitored, and maintained in production-grade environments.

Your tasks:

1. Perform Data & ML Platform Management including workspace configuration, cluster setup, job orchestration, model deployment endpoints, and secure secret or key management as well as configure and manage Unity Catalog for secure and governed data access.
2. Build and maintain ML and CI/CD pipelines for data preparation, training, validation, packaging, and deployment of ML models using platforms like Azure DevOps.
3. Integrate MLflow, Azure ML or equivalent tools for experiment tracking, artifact versioning, and model registry management.
4. Implement monitoring for ML services using Azure Monitor, Application Insights, or open-source tools.
5. Establish end-to-end visibility with logs, metrics, model performance/drift detection, and alerting systems.
6. Design and operationalize safe deployment strategies (blue/green or canary) with rollback mechanisms.
7. Develop Infrastructure as Code (IaC) using Terraform and Bicep for scalable and consistent cloud environments.
8. Support containerized deployments using Docker and Kubernetes for model hosting and inference services.
9. Enforce secure cloud and data operations using tools like Wiz, CrowdStrike, and SonarQube and apply ITIL-based processes for incident, change, and problem management in 24x7 environments.

You will be successful in this role if you have:

• 2–5 years of experience in DevOps or MLOps roles or similar
• Strong expertise/understanding of Cloud Services, Azure Databricks, and Azure Machine Learning
• Deep understanding of ML model lifecycle and pipeline automation using CI/CD.
• Strong coding skills with Python
• Proficiency in Kubernetes, Docker, and Linux/Windows system management.
• Familiarity with ML observability, experiment tracking, and deployment rollback techniques.
• Excellent troubleshooting, problem-solving, and communication skills.

Nice-to-Have Skills:

• Azure certifications (AZ-104, AZ-400, DP-100).
• Experience with GitOps, DevSecOps, or MLOps best practices for CI/CD of AI workloads, Terraform, Bicep, and Azure DevOps.
• Working knowledge of IAM, certificate management, and Key Vault security.

Why Unisys?

• Become part of our "Winning Culture" and work on award-winning projects in high-end technological setting
• Corporate Social Responsibility and Inclusion standards are very important to us and go far beyond the usual - especially in the current political climate!
• We offer a company own learning platform! Our goal is to help you realize your individual potential!
• "Wellbeing & Employee Assistance Program": Your (mental) health is important to us and is treated confidentially by a neutral party!
• Solid qualification-, performance- & competence-based remuneration model, attractive pension scheme and various allowances
• Bonus/referral/incentive/recognition programs - we want you to feel appreciated at Unisys!
• Extended health insurance coverage also for private use after 1-year tenure (premium package)
• Hybrid work model (3 days onsite/2 days flexible) and great camaraderie, whilst working with Lithuania and global top talent
• Free parking lots and a bike garage for storage
• Opportunity to work on production-grade AI and ML systems at scale.
• Collaborative and engineering-focused environment encouraging innovation.

Salary: up to 66.800 € based on your competencies and skills

Unisys is proud to be an equal opportunity employer that considers all qualified applicants without regard to age, caste, citizenship, color, disability, family medical history, family status, ethnicity, gender, gender expression, gender identity, genetic information, marital status, national origin, parental status, pregnancy, race, religion, sex, sexual orientation, transgender status, veteran status or any other category protected by law.