MLOps Lead

MarbleX; Delhi; On-site; INR 3,500,000 - 6,000,000; Full time

Job summary

MarbleX is seeking an experienced MLOps Lead to build and manage reliable deployment pipelines and streamline model operationalization for scalable AI/ML solutions in complex environments.

The role requires leading design of MLOps processes, CI/CD for AI/ML deployments, and collaboration with cross-functional teams to improve ML systems’ reliability and monitoring.

Qualifications

• 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.

Responsibilities

• Lead the design and implementation of MLOps processes and deployment pipelines.
• Build and maintain CI/CD 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

Containerization

Microservices

Education

B.Tech / M.Tech / MS in CS, Data Eng, AI or related

Tools

Docker

Kubernetes

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.