About the Role
We are looking for a DevOps Engineer with experience in building and managing CI/CD pipelines, cloud infrastructure, and AI/ML deployment environments. The candidate will work closely with the development and AI research teams to ensure smooth deployment, scalability, and reliability of applications and AI models.
Key Responsibilities
- Design, implement, and maintain CI/CD pipelines for applications and AI/ML workflows.
- Manage and optimize cloud infrastructure on AWS and Azure.
- Deploy and manage AI/ML models and inference services.
- Work with Hugging Face models, transformers, and model hosting workflows.
- Containerize applications using Docker and manage orchestration using Kubernetes (preferred).
- Implement Infrastructure as Code (IaC) using tools such as Terraform or similar.
- Automate deployments, monitoring, and scaling of services.
- Monitor system performance, uptime, logs, and security.
- Troubleshoot infrastructure, deployment, and pipeline issues.
Required Skills
Strong experience with CI/CD tools (GitHub Actions, Jenkins, GitLab CI, etc.)
- Hands-on experience with AWS and/or Azure cloud services
- Experience with Docker and containerized environments
- Familiarity with Hugging Face ecosystem (Transformers, model deployment, inference APIs)
- Knowledge of Linux systems and shell scripting
- Understanding of networking, security, and scalable infrastructure
- Basic knowledge of AI/ML deployment pipelines
Preferred Skills
- Experience with Kubernetes or container orchestration
- Exposure to ML Ops pipelines
- Experience with Azure ML, AWS SageMaker, or GPU workloads
- Knowledge of Python for automation or ML workflows
What We Offer
- Opportunity to work on cutting-edge AI and cloud infrastructure projects
- Exposure to real-world AI model deployment
- Fast-paced environment with strong learning opportunities
Pay: ₹40,000.00 - ₹57,000.00 per month
Work Location: In person
