DevOps-MLOps Engineer | 4+ YOE | AWS, Kubernetes, CI/CD

DevOps Engineer

with a strong background in automating cloud infrastructure, streamlining CI/CD processes, and enabling scalable, secure deployments across cloud-native environments. With proven experience in both MLOps and DataOps, I specialize in building robust and efficient workflows that support the full lifecycle of modern software and data applications.

Experience

I have hands-on experience in MLOps using AWS SageMaker and EKS, helping teams automate the deployment, monitoring, and scaling of machine learning models in production environments. I work closely with data scientists and ML engineers to bridge the gap between model development and real-world deployment, ensuring reproducibility, scalability, and observability at every stage.

In the realm of DataOps, I’ve developed and maintained data pipelines leveraging AWS Glue, S3, and Redshift, focusing on data ingestion, transformation, and storage optimization for analytics and reporting. I understand the critical importance of reliable, well-orchestrated data infrastructure in today’s data-driven applications and have helped organizations ensure data availability, quality, and compliance through well-designed DevOps and DataOps practices.

Skills

Beyond MLOps and DataOps, my expertise spans:

• Infrastructure as Code (Terraform, CloudFormation)
• Containerization (Docker)
• Orchestration (Kubernetes)
• Configuration Management (Ansible)
• CI/CD Automation (Jenkins, GitHub Actions, GitLab CI)

I am passionate about building developer-centric platforms that accelerate innovation while enforcing best practices around security, monitoring, and performance.

Philosophy

Driven by a mindset of continuous improvement, I strive to align DevOps culture with business goals to deliver value faster, with greater reliability. I thrive in fast-paced, cross-functional environments and bring a proactive, solution-oriented approach to every project.