MLOps Engineer - CI/CD Pipeline Implementation

Job Overview :

We are looking for a skilled ML Operations Engineer to manage and optimize machine learning pipelines and production environments. The ideal candidate will have strong experience in deploying, monitoring, and scaling ML models using modern DevOps and containerization tools.

Key Responsibilities :

- Design, build, and maintain scalable ML pipelines for production environments

- Deploy, monitor, and manage machine learning models in production

- Implement CI/CD pipelines for ML workflows and model lifecycle management

- Work with Kubernetes for container orchestration and deployment

- Collaborate with data scientists and engineering teams to operationalize ML models

- Ensure reliability, scalability, and performance of ML systems

- Automate workflows and improve system efficiency

Required Skills & Qualifications :

- 6-8 years of experience in MLOps, DevOps, or related roles

- Strong experience with ML pipeline development and deployment

- Hands-on experience with Kubernetes and containerization tools (Docker)

- Experience in building CI/CD pipelines

- Strong understanding of cloud platforms (AWS/Azure/GCP)

- Proficiency in Python and scripting for automation

Preferred Qualifications :

- Experience with ML frameworks and tools (TensorFlow, PyTorch, MLflow, etc.)

- Knowledge of monitoring tools and logging frameworks

- Familiarity with infrastructure-as-code (Terraform, etc.)