Machine Learning Engineer

We are looking for a highly skilled MLOps Engineer to design, build, and manage end‐to‐end machine learning pipelines and production‐grade ML infrastructure. This role focuses on scalable ML deployment, monitoring, automation, and lifecycle management, while bridging the gap between Data Science, Engineering, and DevOps teams.

If you have strong expertise in ML model deployment, CI/CD for ML, cloud platforms, and Kubernetes, this is an excellent opportunity to work on enterprise‐scale AI/ML systems.

Key Responsibilities-

• Design, build, and maintain CI/CD pipelines for machine learning models and data pipelines

Automate model training, validation, testing, deployment, and rollback

• Deploy ML models as REST APIs / microservices in production environments

Implement model monitoring, data drift detection, and performance tracking

• Manage and optimize cloud infrastructure (AWS / Azure / GCP) for scalability and cost efficiency
• Work closely with Data Scientists, ML Engineers, and Software Engineers to productionize ML solutions
• Ensure ML governance, security, compliance, reproducibility, and version control
• Maintain feature stores, model registries, and ML lifecycle tools. Troubleshoot and debug production ML systems.

Required Technical Skills-

• Python programming for ML and automation
• Machine Learning frameworks: TensorFlow, PyTorch, Scikit‐learn
• MLOps practices and ML lifecycle management
• Docker for containerization and Kubernetes for orchestration
• CI/CD tools: GitHub Actions, Jenkins, Argo CD
• Cloud platforms: AWS / Microsoft Azure / Google Cloud Platform.

Location of posting -

Infosys Ltd. is committed to ensuring you have the best experience throughout your journey with us.

We currently have open positions in a number of locations across India - Bangalore, Pune, Hyderabad, Chennai, Chandigarh, Trivandrum, Indore, Nagpur, Mangalore, Noida, Bhubaneswar, Kolkata, Coimbatore, Jaipur.

While we work in accordance with business requirements, we shall strive to offer you the location of your choice, where possible.