AI Platform Engineer

📋 Description

• Architect and manage Kubernetes clusters for AI/ML workloads.
• Implement Run:ai and GPU scheduling operators.
• Develop Python automation scripts and ML pipelines.
• Automate infrastructure provisioning with Terraform and Ansible.
• Establish MLOps practices for lifecycle, CI/CD, and monitoring (MLflow).
• Create and manage Jupyter Notebooks for experimentation.

🎯 Requirements

• Strong Python proficiency and ML frameworks (TensorFlow, PyTorch).
• Kubernetes and container orchestration experience.
• Familiarity with Run:ai or similar GPU scheduling platforms.
• Terraform and Ansible for infrastructure automation.
• Experience with Jupyter Notebooks for ML development.
• MLOps tools (MLflow, Kubeflow) and model lifecycle.

🎁 Benefits

• Comprehensive health insurance coverage.
• Paid time off and holidays.
• Flexible work arrangements.
• Learning and development opportunities.
• Employee wellness initiatives.
• Retirement and statutory benefits.