**We are:** Wizeline, a global AI\-native technology solutions provider, develops cutting\-edge, **AI\-powered** digital products and platforms. We partner with clients to leverage data and AI, accelerating market entry and driving business transformation. As a global community of innovators, we foster a culture of **growth, collaboration,** and **impact.** **With the right people and the right ideas, there’s no limit to what we can achieve** **Are you a fit?** Sounds awesome, right? Now, let’s make sure you’re a good fit for the role: ***Key Responsibilities:*** * Design and develop MLOps pipelines for model training, deployment, and retraining. * Containerize models using Docker and deploy via Azure Databricks or AKS. * Implement CI/CD workflows with MLflow and GitHub Actions. * Monitor model performance and data drift using Azure\-native tools. * Collaborate with Data Scientists and Engineers to integrate models into business systems. * Document, standardize, and optimize ML deployment processes. ***Must\-have Skills:*** * Bachelor's in Computer Science, Data Engineering, or a related field. * 3–5 years of experience in MLOps, ML Engineering, or DevOps for ML. * Proficient in Spark and MLflow; strong experience in Databricks and Azure ML. * Solid Python and SQL skills; knowledge of containers (Docker/Kubernetes). * Familiar with CI/CD concepts and tools like Azure DevOps or GitHub Actions. ***Nice\-to\-have:*** * Familiarity with Kubernetes (AKS), Terraform, and model observability practices. * Experience deploying Power BI dashboards that consume predictions. **What we offer:** * A High\-Impact Environment * Commitment to Professional Development * Flexible and Collaborative Culture * Global Opportunities * Vibrant Community * Total Rewards * *Specific benefits are determined by the employment type and location.* Find out more about our culture here.