Artificial Intelligence Engineer

NineTech; New South Wales; On-site; AUD 90,921 - 129,494; Part time

Job summary

A leading company in Sydney is seeking an AI Operations Specialist for a 6-month contract. This part-time role involves deploying and optimizing AI/ML models, ensuring system performance, and collaborating with teams to enhance AI infrastructure. Ideal candidates will have a strong background in machine learning and data operations, with experience in GPU-accelerated environments. Join us to drive innovation in AI technologies.

Qualifications

• Experience deploying and maintaining AI/ML models in production.
• Proficient in ML frameworks and strong programming skills in Python.
• Excellent problem-solving abilities and strong communication skills.

Responsibilities

• Deploy machine learning models into production environments.
• Monitor and maintain model performance for ongoing accuracy.
• Collaborate with IT and DevOps teams to support system reliability.

Skills

Machine Learning

Data Operations

Systems Engineering

Problem Solving

Communication

Education

Bachelor’s degree in Computer Science

Master’s degree in a related field

Tools

TensorFlow

PyTorch

scikit-learn

AWS

Azure

GCP

Docker

Kubernetes

Prometheus

Grafana

Job description

This range is provided by NineTech. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

A$80.00/hr - A$80.00/hr

Direct message the job poster from NineTech

Job Title: AI Operations Specialist (Contract)

Location: Sydney, Australia (On-site, 3 days/week)

Contract Duration: 6 months

Role Overview

We are seeking an experienced AI Operations Specialist for a 6-month contract role based in Sydney. This part-time position (3 days/week) focuses on the deployment, maintenance, and optimization of AI/ML models and supporting infrastructure. The ideal candidate will combine machine learning, data operations, and systems engineering expertise, with practical knowledge of Dell hardware solutions and experience optimizing AI workloads using GPU-accelerated environments.

Key Responsibilities

AI/ML Model Operations

• Deploy machine learning models into production environments.
• Monitor and maintain model performance, ensuring ongoing accuracy and efficiency.
• Implement automated model retraining and updates where applicable.

System Monitoring & Troubleshooting

• Create and manage monitoring tools to track AI system health and performance.
• Troubleshoot and resolve system issues to minimize downtime.
• Collaborate with IT and DevOps teams to support system reliability and uptime.

Performance Optimization

• Analyze and improve the performance of AI systems, reducing latency and increasing throughput.
• Optimize workflows, resource usage, and system architecture for scalable AI operations.
• Apply best practices in GPU usage and compute resource management.

Data Management

• Oversee data pipelines, ensuring high-quality and well-governed data feeds into AI models.
• Collaborate with data engineers to design reliable data infrastructure.
• Maintain compliance with data privacy and security standards.

Documentation & Reporting

• Document operational procedures, deployment steps, and issue resolutions.
• Produce performance and incident reports for stakeholders.
• Contribute to developing operational guidelines and best practices.
• Work closely with data scientists, engineers, and business teams to align on technical solutions.
• Provide operational support and knowledge sharing across teams.
• Stay informed of AI/ML trends and technologies to inform decision-making.

Hardware & Platform Expertise

• Utilize Dell technologies, including servers, storage, and networking equipment, to support AI infrastructure.
• Optimize model performance in GPU-powered environments and recommend hardware upgrades as needed.
• Monitor advancements in relevant hardware technologies to maintain system efficiency.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.
• Demonstrated experience deploying and maintaining AI/ML models in production.
• Proficient in ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Strong programming skills in Python (preferred), Java, or R.
• Experience with cloud environments (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Familiarity with monitoring tools like Prometheus or Grafana.
• Excellent problem-solving abilities and the capacity to work independently.
• Strong communication skills and the ability to collaborate effectively across teams.

Preferred Qualifications

• Master’s degree in a related field.
• Certifications in AI/ML or cloud technologies (e.g., AWS Certified Machine Learning – Specialty).
• Experience with big data ecosystems (Hadoop, Spark).
• Familiarity with MLOps frameworks and tools (MLflow, Kubeflow).

Seniority level

• Seniority level

  Associate

Employment type

• Employment type

  Contract

Job function

• Job function

  Information Technology

• Industries

  IT Services and IT Consulting

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