Deskripsi Pekerjaan
Are you passionate about bridging the gap between cutting-edge AI research and robust production infrastructure? Morgan McKinley is seeking a highly skilled DevOps Engineer specializing in AI to join our forward-thinking team in Putrajaya. In this role, you will be the backbone of our AI initiatives, designing and maintaining scalable cloud architectures that power machine learning models at scale.
You will work at the intersection of traditional DevOps and MLOps, ensuring that our AI-driven cloud platforms are secure, highly available, and optimized for performance. We are looking for an engineer who thrives in dynamic environments, enjoys automating complex workflows, and is committed to building resilient systems that enable rapid innovation.
Tanggung Jawab
- Architect, deploy, and manage scalable AI/ML infrastructure on cloud platforms (AWS/Azure/GCP).
- Implement and maintain MLOps pipelines to automate model training, testing, and deployment cycles.
- Manage container orchestration using Kubernetes to ensure high availability for production AI services.
- Collaborate with Data Scientists to optimize resource allocation and model inference performance.
- Develop and enforce infrastructure-as-code (IaC) standards using Terraform or Ansible.
- Monitor system performance, implement logging, and troubleshoot production issues in real-time.
- Enhance security and compliance protocols across all AI environments.
Kualifikasi
- Bachelor’s degree in Computer Science, Engineering, or a related technical field.
- 3+ years of experience in DevOps or Site Reliability Engineering (SRE) roles.
- Strong hands-on experience with Kubernetes, Docker, and containerized deployment strategies.
- Proficiency in cloud architecture (AWS, Azure, or Google Cloud Platform).
- Experience with MLOps tools (e.g., MLflow, Kubeflow, or SageMaker) is highly desirable.
- Deep understanding of CI/CD pipeline integration and automation scripting (Python, Bash, or Go).
- Solid background in Linux system administration and network security best practices.