DevOps Engineer
Model N
Job Responsibilities
- Develop, deploy, monitor, optimize and maintain build and release pipelines.
- Support developments teams on branching and versioning approaches
- Creating packages, builds, releases and patches as well as the software deliverables for the customers.
- Assist in the design, implementation, and management of DevOps pipelines for deploying and maintaining AI models and services.
- Automate the deployment of AI applications and models into cloud environments (AWS, Azure, GCP, etc.).
- Work with AI and Data Science teams to ensure seamless integration of machine learning workflows into production environments.
- Implement CI/CD pipelines for continuous testing and deployment of AI models and applications.
- Collaborate with cross-functional teams to troubleshoot and resolve issues related to the integration of AI models, data pipelines, and infrastructure.
- Support infrastructure as code (IaC) practices using tools like Terraform, Ansible, or CloudFormation.
- Maintain and optimize cloud infrastructure for cost-efficiency and scalability, particularly for AI workloads.
- Participate in the implementation of containerization and orchestration technologies (Docker, Kubernetes) for All applications.
- Stay updated with the latest trends in DevOps and AI, recommending best practices for improvement.
- Work with QA teams to improve efficiency of automation runs by exploring innovative approaches like parallelization/auto scaling etc.
Job Qualification
- BE/BTech or ME/MTech with 2+ years of experience in DevOps.
- Strong knowledge of DevOps concepts, continuous integration, continuous deployment, and automation.
- Experience with cloud platforms (AWS, GCP, Azure) and cloud services (EC2, Lambda, Kubernetes, etc.).
- Familiarity with containerization tools such as Docker and Kubernetes.
- Exposure to AI/ML concepts, including deployment of machine learning models and managing AI workloads.
- Proficiency in scripting languages (Python, Shell, Bash, etc.).
- Experience with infrastructure as code (IaC) using tools like Terraform, Ansible, or CloudFormation.
- Basic knowledge of version control systems (Git).
- Familiarity with monitoring and logging tools such as Prometheus, Grafana, ELK Stack, or similar.
- Understanding of data pipeline and ETL processes for AI and ML systems.
- Strong analytical and problem-solving skills.
- Excellent communication and collaboration skills.
- Ability to work in a fast-paced and evolving environment.
- A passion for learning new technologies and growing in the DevOps and AI space.