MLOps Lead

MarbleX; Delhi; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

MarbleX is seeking an experienced MLOps Lead to build and manage reliable machine learning deployment pipelines, streamline model operationalization, and support scalable AI/ML solutions within enterprise environments.

You will lead the design and implementation of MLOps processes, build CICD pipelines, and collaborate with data scientists, ML engineers, and DevOps teams to ensure robust, scalable model deployments across complex systems.

Qualifications

• B.Tech, M.Tech, or M.S. in Computer Science, Data Engineering, AI, or a related discipline.
• Certifications in cloud DevOps or MLOps platforms, such as AWS DevOps Engineer, Azure DevOps Expert, or GCP Professional ML Engineer, are highly desirable.
• Contributions to MLOps or DevOps open-source projects are preferred.

Responsibilities

• Lead the design and implementation of MLOps processes and deployment pipelines.
• Build and maintain CICD pipelines for AI/ML model deployment.
• Enable automation across model development, testing, deployment, monitoring, and updates.
• Implement and manage containerized and microservice-based architectures.
• Collaborate with data scientists, ML engineers, and DevOps teams to streamline model deployment.
• Improve the scalability, reliability, and operational efficiency of ML systems.
• Establish monitoring and maintenance practices for deployed models and pipelines.

Skills

MLOps

CI/CD

DevOps

ML systems

Education

B.Tech/M.Tech/M.S. in CS/Data AI

Tools

Docker

Kubernetes

CI/CD tools

Job description

We are seeking an experienced MLOps Lead to build and manage reliable machine learning deployment pipelines, streamline model operationalization, and support scalable AI/ML solutions within enterprise or government environments.

Key Responsibilities

• Lead the design and implementation of MLOps processes and deployment pipelines.
• Build and maintain CICD pipelines for AI/ML model deployment.
• Enable automation across model development, testing, deployment, monitoring, and updates.
• Implement and manage containerized and microservice-based architectures.
• Collaborate with data scientists, ML engineers, and DevOps teams to streamline model deployment.
• Improve the scalability, reliability, and operational efficiency of ML systems.
• Establish monitoring and maintenance practices for deployed models and pipelines.

Required Qualifications

• B.Tech, M.Tech, or M.S. in Computer Science, Data Engineering, AI, or a related discipline.
• Certifications in cloud DevOps or MLOps platforms, such as AWS DevOps Engineer, Azure DevOps Expert, or GCP Professional ML Engineer, are highly desirable.
• Contributions to MLOps or DevOps open-source projects are preferred.

Required Experience

• 7–10 years of experience in machine learning operations or DevOps engineering.
• Minimum 4 years of experience building CI/CD pipelines for AI/ML model deployment in enterprise or government ecosystems.
• Proven experience with containerized and microservice architectures.