Senior MLOps Technical Lead

About the role

This role is accountable for driving advanced machine learning operations and automation within development projects. The individual leverages expertise in ML Ops, DevOps, and Python to architect, implement, and optimize robust ML pipelines, ensuring efficient model deployment, monitoring, and scalability.

What you'll do

• Implement and optimize ML pipelines using MLflow, Kubeflow Pipelines, and TFX, enabling automated model training, validation, and deployment
• Integrate DevOps practices with Python scripting to automate infrastructure provisioning via Terraform, AWS CloudFormation, and Ansible for scalable ML environments
• Configure and maintain CI/CD workflows using Jenkins, GitLab CI/CD, CircleCI, and GitHub Actions to streamline code integration and deployment for ML projects
• Monitor and analyze ML system performance using Prometheus, Grafana, ELK Stack, and Fluentd, ensuring reliability and rapid issue resolution
• Apply advanced proficiency in Git, GitHub, GitLab, and Bitbucket for source code management and collaboration within the development team

What you need

• 6–10 years in data science & ai
• MLOps
• Machine learning
• Python
• AWS
• CI/CD
• Git
• Any graduate

Good to have

• Terraform
• Ansible
• Jenkins
• Prometheus
• Grafana
• Elasticsearch

What you get