Hybrid AI Operations Lead | MLOps & Production AI

Placements24; Queenstown; Hybrid; NZD 98,000 - 163,000; Full time

Job summary

Placements24 is seeking an AI Operations Manager in Queenstown to oversee deployment, monitoring, and maintenance of AI/ML models in production. The role combines technical leadership with hands-on operations to ensure reliable, scalable AI systems.

You will implement MLOps best practices, manage CI/CD pipelines, containerization (Docker, Kubernetes), and cloud resources across AWS/Azure/GCP while collaborating with data scientists, ML engineers, and software developers. Hybrid work is available.

Qualifications

• Bachelor's degree in CS, engineering, or related field.
• Proven experience in production ML systems or MLOps.
• Strong CI/CD, containerization, and cloud platform knowledge.
• Experience with AI/ML monitoring tools.
• Scripting in Python or Bash.
• Excellent problem-solving and analytical skills.
• Strong PM and communication abilities.
• Experience managing hybrid work environments.

Responsibilities

• Oversee deployment, monitoring, and maintenance of AI/ML models in production.
• Develop and implement MLOps CI/CD practices.
• Manage infrastructure and tooling for AI model operations (cloud, containers).
• Monitor performance, detect drift, retrain/update as needed.
• Collaborate with data scientists, ML engineers, and software developers.
• Develop and maintain operational dashboards and reporting.
• Ensure reliability, scalability, and security of AI systems.
• Troubleshoot operational issues related to AI deployments.

Skills

Production ML systems

MLOps

CI/CD pipelines

Containerization

Cloud platforms

Monitoring AI/ML models

Scripting (Python, Bash)

Problem-solving

Project management

Communication

Hybrid work experience

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

Docker

Kubernetes

AWS

Azure

GCP

Job description

Placements24 is seeking an AI Operations Manager in Queenstown to oversee deployment, monitoring, and maintenance of AI/ML models in production. The role combines technical leadership with hands-on operations to ensure reliable, scalable AI systems.

You will implement MLOps best practices, manage CI/CD pipelines, containerization (Docker, Kubernetes), and cloud resources across AWS/Azure/GCP while collaborating with data scientists, ML engineers, and software developers. Hybrid work is available.