MLOps Engineer

About the role

The MLOps / Infrastructure Engineer – AI Security is responsible for building, operating, and scaling the infrastructure and ML pipelines that support AI security research and production systems. The role ensures that AI models, datasets, experiments, and security evaluations are reproducible, observable, and deployable in a secure and compliant manner.

What you'll do

• Design, build, and maintain ML pipelines for model training, evaluation, and AI security testing
• Own infrastructure for experimentation, benchmarking, and large-scale model analysis
• Integrate AI security checks (e.g., scanning, verification, unlearning workflows) into ML pipelines
• Manage compute, storage, and orchestration environments for research and platform workloads
• Ensure reproducibility, traceability, and auditability of models, data, and experiments

What you need

• 8–10 yrs of experience
• MLOps
• Machine learning
• Cloud security
• Docker
• Kubernetes
• B.Tech or B.E. or B.Sc or BCA or M.Tech or MCA or M.Sc

Good to have

• Python