MLOps Engineer - CI/CD Pipeline

Job Title : MLOps Engineer

Experience Required : 5+ Years

Work Mode : Hybrid

Locations : Gurgaon, Pune, Bhopal, Jaipur, Bangalore

Notice Period : Immediate joiners or candidates who have completed their notice period only

About the Role :

We are looking for an experienced and driven MLOps Engineer to join our dynamic team at Deqode. This role demands expertise in deploying machine learning models into production and managing the complete ML lifecycle using AWS services. You will be responsible for designing, implementing, and maintaining scalable MLOps pipelines, with a strong focus on automation, monitoring, and model governance.

Key Responsibilities :

- Design, develop, and maintain MLOps pipelines for deploying and managing machine learning models in production.
- Implement core MLOps concepts such as :

- Model Training, Feature Engineering, Model Registration, Endpoint Deployment, Batch Inference, Model Monitoring, Data Drift Detection.

- Build scalable and secure ML pipelines using AWS SageMaker, Lambda, API Gateway, and other AWS services.

- Use Docker and YAML to containerize and configure the ML workflows.

- Set up and manage CI/CD pipelines using GitLab, incorporating best practices such as : Artifact Scanning, Vulnerability Checks, Automated Testing & Deployment.

- Develop infrastructure using AWS CDK (Cloud Development Kit) to provision and manage AWS resources programmatically.

- Collaborate with Data Scientists, DevOps, and Engineering teams to ensure seamless integration of models into production environments.

- Contribute to MLOps research and help implement cutting-edge techniques for scalable ML operations.

- Participate in system monitoring, debugging, incident management, and performance tuning for ML systems.

Key Skills Required :

- Minimum 5 years of experience in Software Engineering and MLOps.

- Hands-on development experience with AWS, especially SageMaker (mandatory).

- Practical knowledge of MLflow, GitLab, and AWS CDK (mandatory).

- Familiarity with AWS Lambda, Docker, API Gateway, and YAML scripting.

- Proficiency in one or more programming languages : Python, R, Scala, or Spark.

- Strong understanding of production-grade ML systems including security, scalability, and monitoring.

- Good exposure to CI/CD best practices using GitLab CI Pipelines.

- Understanding of artifact scanning and vulnerability assessment in CI/CD environments.

- Exposure to AWS DataZone is a plus.

- Strong analytical mindset and interest in contributing to research and innovation in MLOps.