Description : We are seeking a skilled ML Ops Engineer to join our team and drive the operationalization of machine learning models into production. The ideal candidate will have a solid background in machine learning pipelines, cloud platforms, and DevOps practices, ensuring that AI solutions are scalable, reliable, and secure.Key Responsibilities :- Design and implement robust and scalable ML pipelines on Azure (using Azure ML, Azure Data Factory, Azure DevOps, etc.)- Automate model training, validation, deployment and retraining workflows.- Manage and monitor models in production (versioning, drift detection,



retraining triggers).- Implement CI/CD pipelines tailored for ML workloads.- Exposure on Integrating LLMs into applications with frameworks like LangChain.- Implementation of Orchestration framework for building and managing agentic System.- Collaborate with Data Science and Engineering teams to ensure smooth integration of models with applications and APIs.- Handle data ingestion and transformation pipelines using Azure Data Lake, Databricks, or Synapse.- Apply best practices in security, performance, and cost optimization in Azure cloud environments.- Troubleshoot and resolve deployment and model performance issues.Qualification :- Bachelors in Engineering- 5+ yrs Experience in DevOps + MLOps- Experience in deploying ML models (ref:hirist.tech)

📌 MLOps Engineer (Bengaluru)
🏢 Katalytx Analytics
📍 Bengaluru