MLOps Engineer – AI Automation & Infrastructure (Cognizant)

About Cognizant: Engineering Modern Businesses

Cognizant (Nasdaq-100: CTSH) engineers modern businesses. We help our clients modernise technology, reimagine processes, and transform experiences so they can stay ahead in our fast-changing world. Together, we’re improving everyday life for millions across the globe.

At Cognizant, we don’t just build applications; we build the future of intelligent enterprise through automation, cloud-native architecture, and cutting-edge AI.

The Role: MLOps Engineer (AIA Hub)

We are seeking a high-calibre MLOps Engineer to join our Artificial Intelligence and Analytics (AIA) division in Noida. In this role, you will be the bridge between data science and production engineering, ensuring that our AI models are not just research prototypes but scalable, high-performing business assets.

You will research, implement, and evangelise MLOps tools and frameworks to raise the AI maturity of the organisation through automation and agile practices.

🎯 Key Responsibilities

• Infrastructure & Architecture: Design and lead the MLOps Architecture for large-scale data science projects.

• Pipeline Engineering: Build and maintain end-to-end Deployment, Inference, Monitoring, and Retraining pipelines.

• Operational Excellence: Implement CI/CD/CT (Continuous Testing) pipelines to automate the software and model lifecycle.

• Monitoring & Drift: Set up robust systems for Drift Detection, specifically monitoring for Data Drift and Model Drift post-deployment.

• Model Management: Manage Experiment Tracking and publish REST APIs for seamless model consumption.

• Evangelism: Conduct internal training and presentations to drive a modern, automated approach to Data Science across the firm.

💪 Required Experience & Qualifications

• Experience: 3 to 12 years of hands-on experience in MLOps and Machine Learning infrastructure.

• Cloud & Containerization: Wide experience with Kubernetes is mandatory. Proficiency in AWS (preferred), GCP, or Azure.

• MLOps Platforms: Hands-on experience with at least one major platform: Kubeflow, AWS SageMaker, Azure ML, or Google AI Platform.

• Programming: Proficiency in Python for both ML tasks and automation. Solid knowledge of Bash and the Unix toolkit.

• Core Concepts: Good understanding of AI/ML concepts with practical experience in model development.

• Automation: Demonstrated experience in building automated retraining and monitoring pipelines.

Why Join Cognizant?

• Modernise at Scale: Work on high-impact projects that transform processes for the world’s leading organisations.

• AI Maturity: Lead the charge in shifting a global enterprise toward an automated “AI-first” mindset.

• Career Growth: Opportunities for technical leadership and specialisation in cloud-native AI infrastructure.

• Global Network: Collaborate with a diverse team of engineers and scientists across the CTSH global network.

How to Apply

Ready to automate the future of AI?

Location: Noida (AIA Hub)

Experience Level: 3–12 Years

Apply Now: https://www.linkedin.com/jobs/search-results/?currentJobId=4325350377&eBP