We are seeking a talented Google Cloud Engineer with 2 to 5 years of experience to join our team. The ideal candidate will have a strong background in Google Cloud Platform (GCP), DevOps practices, MLOps, and Kubernetes. This role involves designing, implementing, and maintaining scalable cloud infrastructure, automating workflows, and supporting machine learning operations.
**Key Responsibilities:**
– **Google Cloud Platform (GCP) Management:**
- Design, deploy, and manage GCP services including Compute Engine, Cloud Storage, BigQuery, and Cloud SQL.
- Optimize cloud infrastructure for performance, security, and cost-efficiency.
**DevOps:**
- Implement CI/CD pipelines using tools such as Jenkins, GitLab CI, or Google Cloud Build.
- Automate infrastructure provisioning and application deployment using Infrastructure as Code (IaC) tools like Terraform or Google Cloud Deployment Manager.
- Monitor system performance and troubleshoot issues to ensure high availability and reliability.
– **MLOps:**
- Support the deployment, scaling, and management of machine learning models on GCP.
- Work with data scientists to operationalize machine learning workflows and integrate them into production environments.
- Implement monitoring and logging solutions for machine learning models to ensure they perform optimally.
– **Kubernetes:**
- Manage and orchestrate containerized applications using Kubernetes.
- Deploy, scale, and maintain Kubernetes clusters on GCP.
- Develop and manage Helm charts for application deployments.
– **Collaboration and Support:**
- Work closely with development teams to understand application requirements and provide cloud solutions.
- Document processes, configurations, and best practices for team knowledge sharing.
- Provide technical support and troubleshoot complex issues related to cloud infrastructure and services.
**Qualifications:**
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
- 3 to 7 years of hands-on experience with Google Cloud Platform (GCP).
- Strong experience with DevOps practices and tools (CI/CD, IaC, pulumi with typescript).
- Proficiency in Kubernetes for container orchestration.
- Experience with MLOps, including deploying and managing machine learning models in a cloud environment.
- Strong scripting skills (e.g., Python, Bash, or Go).
- Familiarity with monitoring and logging tools (e.g., Prometheus, Grafana).
- Excellent problem-solving skills and ability to troubleshoot complex issues.
- Strong communication skills and the ability to work effectively in a team environment.
**Preferred Qualifications:**
- Google Cloud Professional Architect or Google Cloud Professional Data Engineer certification.
- Experience with additional cloud providers (e.g., AWS, Azure).
- Knowledge of additional container orchestration tools or serverless architectures.
- Experience with security best practices in cloud environments.