Job Description
Position Overview We are seeking a
Lab Manager with expertise in containerization and AI infrastructure to lead the setup, management, and optimization of containerized environments for AI development and testing. This role will focus on building and maintaining scalable, efficient, and high-performance lab environments to support AI-driven applications. The ideal candidate will have experience managing lab operations, designing container-based architectures, and collaborating with stakeholders to ensure seamless integration of AI workloads.Key Responsibilities Lab Management & Infrastructure
- Oversee the setup, configuration, and ongoing management of lab environments, including containerized AI workloads.
- Maintain hardware and software resources, ensuring high availability and performance for AI research and development.
- Implement best practices for container orchestration (Docker, Kubernetes) to support AI workloads efficiently.
- Manage resource allocation for compute-intensive AI tasks, optimizing GPU, CPU, and storage usage.
Containerization & System Architecture - Design and implement containerized environments for AI applications, ensuring scalability and security.
- Utilize Kubernetes, Docker, and other orchestration tools to deploy and manage containerized AI models.
- Develop automated workflows for building, testing, and deploying AI models within a containerized infrastructure.
- Ensure integration with cloud and on-prem infrastructure for hybrid AI workloads.
Collaboration & Stakeholder Engagement - Work closely with data scientists, AI engineers, and IT teams to understand infrastructure requirements.
- Provide technical leadership on best practices for AI containerization and lab infrastructure.
- Conduct knowledge-sharing sessions to educate teams on containerization strategies and deployment methodologies.
Security & Compliance - Implement security best practices for containerized environments, including RBAC, encryption, and vulnerability management.
- Ensure compliance with industry standards and internal policies for AI research and development.
- Monitor and enforce access controls to protect sensitive AI datasets and computing resources.
Documentation & Support - Maintain detailed documentation for lab setups, configurations, and container orchestration strategies.
- Provide troubleshooting and technical support to AI teams using the lab environment.
- Continuously optimize container performance, resource utilization, and system reliability.
Qualifications Education:
- Bachelor's degree in Computer Science, Engineering, or a related field (Master's degree preferred).
Experience: - 5+ years of experience in IT infrastructure, containerization, or AI-focused lab management .
- Hands-on experience with Kubernetes, Docker, OpenShift, or other container orchestration platforms .
- Strong background in Linux system administration and networking in a lab or enterprise setting.
- Experience working with AI/ML frameworks (TensorFlow, PyTorch, etc.) in containerized environments.
Skills: - Expertise in container orchestration and deployment automation (Helm, Terraform, Ansible).
- Knowledge of GPU acceleration and resource scheduling for AI workloads .
- Proficiency in monitoring and logging tools (Prometheus, Grafana, ELK Stack) .
- Strong scripting skills ( Python, Bash, YAML ) for automation and system configuration.
- Excellent problem-solving and troubleshooting abilities.
Preferred Certifications: - Certified Kubernetes Administrator (CKA) or Certified Kubernetes Application Developer (CKAD) .
- Docker Certified Associate (DCA) .
- Red Hat Certified Engineer (RHCE) or equivalent Linux certification.
MetroSys
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