MLOps Engineer

MLOps / Infrastructure - AI Security (Top Tier Institutes Only)

Experience : 5 - 8 Years

Job Location : Bengaluru

Budget : Open

AI Security Mandatory

About the Role :

We are looking for an experienced MLOps / ML Infrastructure professional to build, automate, monitor and secure production-grade AI/ML infrastructure. The role sits at the intersection of MLOps, cloud infrastructure, platform engineering and AI Security, with a strong focus on reliable and secure ML systems.

Key Responsibilities :

- Design, build and maintain end-to-end MLOps infrastructure and ML pipelines.

- Develop automated workflows for model development, validation, deployment and monitoring.

- Build and manage containerized ML workloads using Docker and Kubernetes.

- Implement workflow orchestration for ML training and deployment pipelines.

- Set up model monitoring, experiment tracking, model registry and data/model versioning.

- Build and maintain CI/CD pipelines for ML applications, models and infrastructure.

- Implement infrastructure automation and scalable cloud infrastructure for AI/ML workloads.

- Integrate AI/ML security controls and validation checks across the ML lifecycle.

- Support secure model deployment, access control, secrets management and infrastructure security.

- Collaborate with AI/ML, cloud, DevOps and security teams to improve platform reliability and security.

- Troubleshoot infrastructure, pipeline, deployment and production issues.

Required Skills & Experience :

- MLOps / ML Infrastructure : Strong hands-on experience building and operating production ML platforms.

- AI Security : Mandatory hands-on understanding of securing AI/ML systems, pipelines, models, data or GenAI workloads.

- Containers & Orchestration : Kubernetes and Docker.

- ML Pipelines : Experience with automated training, validation, deployment and monitoring workflows.

- ML Lifecycle : Model monitoring, experiment tracking, model registry and versioning.

- Cloud : Experience with AWS, Azure or GCP cloud infrastructure.

- CI/CD : Experience building automated CI/CD pipelines for ML/software workflows.

- Infrastructure Automation : Experience with automation and Infrastructure as Code practices.

Good to Have :

- Experience with MLflow, Kubeflow, Airflow, Argo Workflows or similar MLOps/orchestration platforms.

- Knowledge of Kubernetes security, cloud-native security and DevSecOps.

- Experience with LLM/GenAI deployment and security.

- Exposure to model scanning, vulnerability assessment, data validation and AI security testing.

- Experience with Terraform or similar Infrastructure as Code tools.

- Experience with observability, logging, monitoring and alerting frameworks.

Preferred Educational Background :

- Candidates from premier institutes in Technology, Cybersecurity, Mathematics or Cryptography are preferred. Preferred institutes include IISc, IITs, NIT Trichy, NIT Warangal, IIIT Allahabad, IISERs, Indian Statistical Institute, Chennai Mathematical Institute, Madras Institute of Mathematics, and other strong institutes in relevant domains.

Candidate Profile :

- Ideal candidates will combine strong MLOps / ML infrastructure experience with practical AI Security exposure. Candidates should be comfortable working across ML pipelines, cloud infrastructure, containers, orchestration, automation and production security.

Skills

MLOps, Security Architect - AI, ML Infrastructure, Cloud Infrastructure, CI/CD Pipeline, Docker, Kubernetes, IT Infrastructure Automation, DevSecOps, Cloud Security