MCI, a fast-growing tech-enabled business services company specializing in Customer Experience (CX) and BPO, is seeking an AI Systems Administrator. This role is critical for supporting, maintaining, and optimizing the infrastructure that powers the company’s artificial intelligence and machine learning environments.

This is a Full-time position in the US with a salary range of $60,000.00 – $80,000.00/Yr.

Position Overview and MLOps Mandate

This administrator bridges the gap between technical operations and advanced AI innovation, ensuring the reliability, scalability, and security of AI systems, models, and related data pipelines.

Key Responsibilities:

• System & Resource Management: Oversee, configure, and monitor AI and ML systems, servers, and cloud environments. Manage GPU/CPU clusters to ensure efficient resource allocation for training and inference workloads.
• Infrastructure Optimization: Implement and maintain scalable infrastructure for large language models (LLMs), data processing pipelines, and model deployment. Optimize system performance through tuning and automation.
• Deployment & Integration: Support the deployment and integration of AI models and APIs into production environments. Support CI/CD pipelines for AI model updates and system maintenance.
• Security & Compliance: Apply best practices for securing AI systems, ensuring data integrity and compliance. Manage user access, permissions, and security configurations.
• Monitoring & Troubleshooting: Monitor system health and performance metrics; diagnose and resolve infrastructure or software issues. Conduct root cause analysis.
• Automation & Scripting: Develop scripts and tools using Python/Bash to automate system tasks, data transfers, and performance checks.
• Collaboration: Collaborate with developers, data scientists, and prompt engineers to ensure seamless system functionality.

Candidate Qualifications

The ideal candidate has a blend of traditional systems administration experience with exposure to MLOps, cloud, and specialized AI computing.

• Education: Bachelor’s degree in Computer Science, IT, Data Engineering, or a related field.
• Experience: 2+ years of experience in systems administration, DevOps, or infrastructure management (AI/ML environment experience preferred).
• Core Technology:
  • Strong understanding of cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
  • Experience with Linux/Unix administration and Python/Bash scripting.
  • Experience with automation tools (Terraform, Ansible, Jenkins).
• AI/ML Specifics: Familiarity with machine learning frameworks (TensorFlow, PyTorch) and AI model deployment pipelines. Understanding of GPU-based computing and performance optimization for AI workloads.
• Systems Knowledge: Understanding of networking, security, and storage in distributed computing environments.