DevOps Engineer
2 months ago
Position Name : DevOps Engineer - AI/ML
Experience Required : 3-6 Years
Notice period : Immediate Joiners Only/ Serving Notice Period
Job Model : Hybrid
Work Mode : 3 Days (WFO), 2 Days (WFH)
Mandatory Skills set : AI/ML, AWS, Azure, CI/CD Pipelines, Git, Docker, Kubernetes,
Overview :
We are seeking a talented DevOps Engineer with a focus on AI/ML to join our dynamic team. The ideal candidate will have experience in designing and implementing scalable infrastructure and managing cloud services that support machine learning workflows.
Job Description :
- Design and implement scalable and robust infrastructure for AI/ML model training and deployment.
- Manage cloud-based infrastructure and services (e.g., AWS, Google Cloud, Azure) to support AI/ML workflows.
- Optimize resource utilization and cost efficiency for AI/ML workloads.
- Develop and maintain CI/CD pipelines to automate the building, testing, and deployment of AI/ML models and applications.
- Integrate version control systems (e.g., Git) with CI/CD pipelines to ensure smooth and efficient code management.
- Implement automated testing and validation steps within CI/CD pipelines to ensure model performance and reliability.
- Use containerization technologies (e.g., Docker) to package AI/ML applications and their dependencies.
- Implement orchestration solutions (e.g., Kubernetes) to manage containerized AI/ML workloads at scale.
- Ensure high availability and reliability of AI/ML services through effective orchestration and monitoring.
Key Responsibilities :
- Infrastructure Design : Architect and implement robust infrastructure for AI/ML model training and deployment, ensuring scalability and reliability.
- Cloud Management : Manage and optimize cloud-based infrastructure (AWS, Google Cloud, Azure) to facilitate efficient AI/ML operations.
- Cost Optimization : Analyze resource utilization and implement strategies for cost efficiency in AI/ML workloads.
- CI/CD Pipeline Development : Create and maintain CI/CD pipelines to automate the building, testing, and deployment processes for AI/ML models and applications.
- Version Control Integration : Integrate version control systems (e.g., Git) with CI/CD processes to ensure effective code management and collaboration.
- Automated Testing : Implement automated testing and validation within CI/CD pipelines to guarantee model performance and reliability.
- Containerization : Utilize containerization technologies (e.g., Docker) to package AI/ML applications along with their dependencies for consistent deployment.
- Orchestration Management : Deploy orchestration solutions (e.g., Kubernetes) to manage and scale containerized AI/ML workloads effectively.
- Monitoring and Reliability : Ensure high availability and reliability of AI/ML services through proactive monitoring and :
- Bachelor's degree in Computer Science, Engineering, or a related field.
- 3 to 6 years of experience in DevOps roles, with a focus on AI/ML.
- Proficiency in cloud services (AWS, Google Cloud, Azure) and experience in managing cloud infrastructure.
- Strong understanding of CI/CD principles and tools.
- Familiarity with version control systems, particularly Git.
- Experience with containerization (Docker) and orchestration (Kubernetes).
- Knowledge of machine learning frameworks and workflows is a plus.
- Excellent problem-solving skills and ability to work in a fast-paced environment.
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