Interesting Job Opportunity: MLOps Engineer

Katalytx Analytics; Hyderabad; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

Katalytx Analytics is looking for a skilled ML Ops Engineer to operationalize machine learning models into production. This role involves designing robust ML pipelines on Azure and automating data workflows.

The ideal candidate has over 5 years of experience in DevOps and MLOps, with a strong background in Azure cloud services. If you are eager to work in a dynamic team, we encourage you to apply.

Qualifications

• 5+ years of experience in DevOps and MLOps.
• Experience deploying machine learning models in production.
• Strong knowledge of Azure cloud services.

Responsibilities

• Design and implement robust and scalable ML pipelines on Azure.
• Automate model training, validation, deployment and retraining workflows.
• Manage and monitor models in production.
• Implement CI/CD pipelines tailored for ML workloads.
• Collaborate with Data Science and Engineering teams.

Skills

Machine learning pipelines

Azure cloud platforms

DevOps practices

CI/CD pipelines

Education

Bachelor’s degree in Engineering or related field

Tools

Azure ML

Azure Data Factory

Azure Data Lake

Databricks

Azure DevOps

LangChain

Job description

ML Ops Engineer

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 strong 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.
• Expose and integrate LLMs into applications with frameworks like LangChain.
• Implement an orchestration framework for building and managing agentic systems.
• 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.

Qualifications

• Bachelor’s degree in Engineering or related field.
• 5+ years of experience in DevOps and MLOps.
• Experience deploying machine learning models in production.
• Strong knowledge of Azure cloud services.