AI Systems Administrator

The Sydney Call Centre

10h•Onsite

About The Position

MCI is a rapidly growing tech-enabled business services company with a significant call center presence and international operations. We provide Customer Experience (CX), Business Process Outsourcing (BPO), and Anything-as-a-Service (XaaS) cloud technology solutions to various industries. Our contact centers utilize both on-site and remote agents, employing advanced technologies to improve customer interactions, scalability, and cost-efficiency. MCI is dedicated to creating a professional environment that supports career development, continuous learning, and the success of a leading global organization. We are looking for a skilled, proactive, and detail-oriented AI Systems Administrator to manage, maintain, and optimize the infrastructure for our artificial intelligence and machine learning environments. This role is crucial for ensuring the reliability, scalability, and security of AI systems, models, and data pipelines, acting as a liaison between technical operations and AI innovation. To be considered, a full application on our company careers page, including screening questions and a pre-employment test, is required.

Requirements

Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related field.
2+ years of experience in systems administration, DevOps, or infrastructure management (AI/ML environment experience preferred).
Strong understanding of cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
Experience with Linux/Unix administration, Python/Bash scripting, and automation tools (Terraform, Ansible, Jenkins).
Familiarity with machine learning frameworks (TensorFlow, PyTorch) and AI model deployment pipelines.
Understanding of networking, security, and storage in distributed computing environments.
Experience with GPU-based computing and performance optimization for AI workloads.
Excellent problem-solving, troubleshooting, and documentation skills.
Strong collaboration and communication abilities to work with cross-functional AI and engineering teams.

Responsibilities

Oversee, configure, and monitor AI and ML systems, servers, and cloud environments for optimal performance and uptime.
Manage GPU/CPU clusters and ensure efficient resource allocation for training and inference workloads.
Implement and maintain scalable infrastructure for large language models (LLMs), data processing pipelines, and model deployment.
Optimize system performance through tuning, automation, and proactive maintenance.
Apply best practices for securing AI systems, ensuring data integrity, confidentiality, and compliance with company and industry standards.
Manage user access, permissions, and security configurations across AI platforms.
Support the deployment and integration of AI models and APIs into production environments.
Collaborate with developers, data scientists, and prompt engineers to ensure seamless system functionality and workflow automation.
Monitor system health, usage, and performance metrics; diagnose and resolve infrastructure or software issues.
Maintain logs, conduct root cause analysis, and implement corrective actions to prevent recurrence.
Develop scripts and tools to automate system tasks, data transfers, and performance checks.
Support CI/CD pipelines for AI model updates and system maintenance.
Create and maintain detailed documentation of system configurations, procedures, and troubleshooting guides.
Provide technical support to AI teams, ensuring smooth operation of all AI systems and tools.
Stay up-to-date with advancements in AI infrastructure, cloud technologies, and MLOps practices.
Recommend and implement improvements to enhance system reliability and scalability.