MLOps Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

Not verified checked Jun 13, 2026

Salary

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401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

Shift type

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Weekend work

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Application

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

MLOps Engineer Vilnius What success looks like in this role: 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: You´ll 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. Build and maintain ML and CI/CD pipelines for data preparation, training, validation, packaging, and deployment of ML models using platforms like Azure DevOps. Integrate MLflow, Azure ML or equivalent tools for experiment tracking, artifact versioning, and model registry management. Implement monitoring for ML services using Azure Monitor, Application Insights, or open-source tools. Establish end-to-end visibility with logs, metrics, model performance/drift detection, and alerting systems. 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: Must-Have-Skills: 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

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