Job Title : Lead MLOps DevOps Engineer.

Work Location : Bangalore, India.

Experience Range : 8 - 12 Years.

What We're Looking For :

This lead-level role owns the design and operation of MLOps and DevOps platforms that support reliable model build, test, deployment, and release workflows.

The position combines cloud-native infrastructure, container orchestration, automation, and production model serving to improve delivery speed, governance, and operational stability across machine learning environments.

Key Responsibilities :

- Design and operate scalable MLOps pipelines that support reliable build, test, deployment, and release processes for machine learning workloads.
- Lead the implementation of cloud-native infrastructure, container orchestration, and automation practices across development and production environments to improve scalability and repeatability.
- Establish monitoring, logging, and alerting standards for model and platform services to improve reliability, performance, and incident response.
- Partner with data science, engineering, and security teams to productionize machine learning workloads with governance, repeatability, and compliance.
- Define deployment standards for model serving, artifact promotion, and workplace parity to reduce release risk and accelerate production adoption.
- Drive technical best practices, mentor engineers on platform automation patterns, and continuously improve delivery speed and operational efficiency.
- Strengthen secrets handling, access controls,



and release governance across CI/CD and runtime environments to improve security and audit readiness.

Must-Have Skills :

- MLOps &
- Model Lifecycle : MLOps, Model deployment and serving.
- Cloud-Native Infrastructure &
- Orchestration : Containers, Kubernetes.
- Delivery Automation &
- Release Engineering : CI/CD pipelines, Artifact and package management.
- Infrastructure Provisioning &
- Security : Infrastructure as Code, Secrets management.
- Monitoring and observability.
- Python.

Technical Skills :

- Operating Systems &
- Scripting : Linux, Bash and Python.
- Version Control &
- Source Management : Gitlab, GitHub.
- Cloud Platforms : AWS (Amazon Web Services).
- Containerization &
- Deployment : Docker, Kubernetes.
- Infrastructure Automation &
- Configuration Management : Terraform, Ansible, CloudFormation.
- CI/CD Platforms : GitLab CI/CD.
- Observability Tools : DataDog or Dynatrace.
- MLOps Platforms &
- Workflow Orchestration : MLflow, Airflow, AWS SageMaker.
- Data &
- API Integration : SQL, REST APIs.
- Cloud Security &
- Access Control : IAM and cloud security controls.

Why Join This Opportunity?

- Own the platform layer that turns machine learning models into reliable production services.
- Influence DevOps and MLOps standards across build, deployment, observability, and governance workflows.
- Work at lead level on cloud-native automation and model-serving patterns that improve release speed and operational stability.

📌 Sonata Software - Lead MLOps DevOps Engineer (India)
🏢 Sonata Software
📍 India