This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a MLOps Engineer based in Brazil.
As an MLOps Engineer, you will design, implement, and maintain automated environments for data products and machine learning models. You will operate at the intersection of Data Engineering, Data Science, and Operations, helping teams move models reliably from experimentation into production. The role focuses heavily on Azure-based data and AI platforms, with responsibility for automation, governance, scalability, and operational reliability. You will work with technologies including Azure Databricks, Spark, Azure Machine Learning, MLflow, Docker, and Kubernetes. Your work will directly support the continuous evolution of analytics and AI solutions in enterprise environments. This is an opportunity to contribute to sophisticated data and AI initiatives while helping establish robust engineering and deployment practices.
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Accountabilities:
Design, implement,



and sustain automated pipelines for data products and machine learning models across development, testing, and production environments.
Act as a technical bridge between Data Engineering, Data Science, and Operations teams to enable reliable delivery of data and ML solutions.
Build and maintain scalable data engineering environments using Azure Databricks and Apache Spark.
Develop and manage data workflows across Azure Data Factory, Azure Data Lake Storage Gen2, and Azure Synapse Analytics.
Implement DataOps practices, including source control, automated deployment, CI/CD, and setting management.
Build and maintain CI/CD pipelines for data and machine learning projects using Azure DevOps, Azure Repos, and Azure Pipelines.
Implement experiment tracking, model versioning, and lifecycle management using MLflow and Azure Machine Learning.
Deploy machine learning models through real-time inference endpoints and batch endpoints, ensuring reliability and

📌 MLOps Engineer (India)
🏢 Jobgether
📍 India