MLOPS Engineer (Nuc Job/ 104)

Job Description – MLOps Engineer

Position: MLOps Engineer
Experience: 5+ Years
Location: Remote 
Shift: US Time Zone (6:30 PM IST – 3:30 AM IST)

 

Job Summary

We are seeking an experienced MLOps Engineer to build, automate, deploy, and manage Machine Learning platforms and production-grade AI solutions. The ideal candidate will have strong expertise in Docker, Kubernetes, Kubeflow, CI/CD, Cloud Platforms, and ML model deployment.

Key Responsibilities

· Design, implement, and maintain scalable MLOps infrastructure and pipelines.

· Automate model training, testing, deployment, and monitoring processes.

· Deploy and manage ML models in production environments.

· Build and maintain CI/CD pipelines for Machine Learning applications.

· Manage containerized workloads using Docker and Kubernetes.

· Develop and optimize ML workflows using Kubeflow.

· Collaborate with Data Scientists, Data Engineers, and Software Engineers to operationalize ML models.

· Monitor model performance, drift, and infrastructure health.

· Implement security, governance, and compliance best practices.

· Troubleshoot and optimize production ML systems.

Required Skills

· 5+ years of experience in MLOps, DevOps, or Machine Learning Engineering.

· Strong hands-on experience with Docker and Kubernetes.

· Experience building ML pipelines using Kubeflow.

· Proficiency in Python and scripting languages.

· Experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or Azure DevOps.

· Knowledge of model deployment, monitoring, and lifecycle management.

· Experience with cloud platforms such as AWS, Azure, or GCP.

· Familiarity with Infrastructure as Code (Terraform, CloudFormation).

· Strong understanding of Linux systems and networking concepts.

· Experience with Git version control.

Education

· Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.