ai - MLOps Cloud Engineer - DevOps

2 weeks ago

Hyderabad, Telangana, India mokSa Full time

About

Based in Hyderabad, is a trailblazer in AI-driven surveillance audit technology. Our platform is tailored to combat shoplifting and employee fraud, offering insights for strategic decisions. We excel in AI-powered customer tracking and employee management, and are known for our resource optimization and Design, deploy, and manage cloud-based infrastructure for machine learning workloads, ensuring scalability, reliability, and performance.

2. Collaborate with data scientists and machine learning engineers to understand model requirements and operationalize machine learning pipelines.

3. Implement CI/CD pipelines for automating the training, testing, and deployment of machine learning models.

4. Develop and maintain monitoring and alerting systems to track the performance and health of deployed machine learning models.

5. Optimize resource utilization and cost-effectiveness of cloud resources used for machine learning tasks.

6. Implement security best practices to protect sensitive data and machine learning models in cloud environments.

7. Work closely with software development teams to integrate machine learning models into production applications.

8. Troubleshoot and resolve issues related to infrastructure, deployment, and performance of machine learning systems.

9. Stay updated with the latest advancements in cloud computing, DevOps tools, and machine learning technologies.

10. Document processes, procedures, and configurations related to machine learning infrastructure and deployment Bachelors degree in Computer Science or related field.

2. 2+ Experience with cloud platforms (AWS) and DevOps practices.

3. Proficiency in scripting languages (Python, Shell scripting).

4. Familiarity with containerization (Docker, Kubernetes) and machine learning frameworks.

5. Strong problem-solving skills and ability to work in a fast-paced environment.

Preferred Qualifications:

1. Certification in AWS and Kubernetes are Preferred

2. Experience with infrastructure automation tools (Terraform, Ansible).

3. Knowledge of machine learning deployment tools (MLflow, Kubeflow).

4. Familiarity with cybersecurity principles for cloud-based systems.

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