Machine Learning Engineers

Talent; South Australia; On-site; AUD 120,000 - 180,000; Full time

Job summary

A leading recruitment firm is seeking an ML Ops professional for an Adelaide-based position. This contract role involves designing and maintaining ML pipelines, ensuring compliance with security frameworks, and collaborating with data professionals. Candidates should have experience in ML Ops roles, with proficiency in cloud platforms and CI/CD tools. This is an excellent opportunity for those looking to advance their career in ML technology while providing mentorship to team members.

Qualifications

• Demonstrated experience in ML Ops or related roles within complex environments.
• Strong knowledge of ML lifecycle management and deployment strategies.
• Solid understanding of data engineering, version control (Git), and automation frameworks.
• Experience with ML Ops tools (Kubeflow/MLflow/Airflow) and CI/CD pipelines.
• Solid understanding of data engineering, version control (Git) and automation frameworks.
• Excellent problem-solving skills and ability to work under pressure.

Responsibilities

• Design, implement, and maintain ML pipelines for model training, deployment, and monitoring.
• Develop automation and CI/CD workflows for ML models.
• Ensure compliance with Australian Government security frameworks and agency policies.
• Provide technical advice and mentorship to team members.
• Collaborate with data professionals to transition models from development to production.
• Implement monitoring and alerting for model performance and data drift.
• Provide technical advice and mentorship to team members and stakeholders.
• Stay current with emerging ML Ops technologies and best practices.

Skills

ML Ops experience

Cloud platforms (AWS, Azure, GCP)

Containerisation (Docker, Kubernetes)

CI/CD pipelines

Data engineering

Problem-solving skills

Automation frameworks

Problem-solving under pressure

Tools

Kubeflow

MLflow

Airflow

Docker

Kubernetes

Git

AWS

Azure

GCP

Job description

Overview

6 months initial contract with possible extension

Adelaide Based Position

Duties and Responsibilities

• Design, implement, and maintain ML pipelines for model training, deployment, and monitoring.
• Develop automation and CI/CD workflows for ML models using tools such as
• Ensure compliance with Australian Government security frameworks (ISM, PSPF) and agency policies.
• Optimise ML infrastructure for performance, scalability, and cost-effectiveness.
• Collaborate with data professionals to transition models from development to production.
• Implement monitoring and alerting for model performance and data drift.
• Provide technical advice and mentorship to team members and stakeholders.
• Stay current with emerging ML Ops technologies and best practices.

Qualifications

• Demonstrated experience in ML Ops or related roles within complex environments.
• Strong knowledge of ML lifecycle management and deployment strategies.
• Proficiency in cloud platforms (AWS, Azure, GCP) and containerisation (Docker, Kubernetes).
• Experience with ML Ops tools (Kubeflow, MLflow, Airflow) and CI/CD pipelines.
• Solid understanding of data engineering, version control (Git), and automation frameworks.
• Excellent problem-solving skills and ability to work under pressure.

Apply now or reach to Ivan Aureus at 0480 806 152 for a confidential chat!