Posted:7 hours ago|
Platform:
Work from Office
Full Time
Job description.
Skills:
Proven experience with CI/CD tools such as Jenkins, GitLab CI/CD, or CircleCI.
Solid hands-on experience with infrastructure as code (IaC) using Terraform, Ansible, or similar tools.
Strong knowledge of Docker and Kubernetes in a production environment.
- Familiarity with ML workflows and AI pipelines (e.g., MLflow, Kubeflow, or SageMaker).
- Experience with monitoring tools like Prometheus, Grafana, ELK Stack, or Datadog.
- Strong scripting skills (Bash, Python).
- Familiarity with data versioning tools (e.g., DVC) is a plus.
Design, implement, and maintain CI/CD pipelines for AI and ML applications.
Collaborate closely with data scientists and AI engineers to support model training, testing, and deployment workflows.
Manage cloud infrastructure (AWS, GCP, or Azure) optimized for AI workloads.
Automate infrastructure provisioning using tools like Terraform or CloudFormation. Ensure system scalability, availability, and performance for AI services.
Monitor AI model performance and infrastructure metrics; set up alerts and dashboards.
Implement security best practices in all DevOps processes.
Support containerization (Docker) and orchestration (Kubernetes) of AI workloads.
Perform root cause analysis and troubleshoot infrastructure issues.
Build and manage scalable infrastructure for AI/ML models in production environments. Ensure robust and repeatable deployment processes for large-scale, real-time AI systems.
CGI
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