Design, build, and maintain scalable and reliable infrastructure for machine learning, data management and software applications.
Develop, implement and maintain CI/CD pipelines to automate the deployment and testing of ML models.
Monitor and manage the performance, availability, and security of ML models and applications in production.
Implement and manage containerization technologies (Docker, Kubernetes) to ensure efficient resource utilization.
Automate infrastructure provisioning and configuration using tools like Terraform, Ansible, or similar.
Manage and maintain ML team’s database.
Ensure best practices for version control, testing, and documentation are followed.
Stay up-to-date with the latest industry trends and technologies in DevOps and MLOps.

3+ years of experience in DevOps, MLOps, or a related role.
Bachelor’s degree in Computer Science, Engineering, or a related field.
Strong knowledge of cloud platforms (AWS, Azure, GCP) and cloud-native services.
Experience with CI/CD tools such as GitHub Actions, GitLab, Jenkins, or similar tools.
Proficiency in containerization technologies (Docker, Kubernetes).
Familiarity with infrastructure as code (IaC) tools like Terraform, Ansible, or CloudFormation.
Database Architecture or Management Experience
Solid understanding of software development lifecycle (SDLC) and Agile methodologies.
Strong scripting skills in Python, Bash, or similar languages.
Excellent problem-solving skills and attention to detail.
Strong communication and collaboration skills.

Machine Learning Operations Engineer

Key skills