Senior Machine Learning Ops Engineer

IT Alliance; City of Brisbane; On-site; AUD 140,000 - 190,000; Full time

Job summary

IT Alliance is seeking a Senior Machine Learning Ops Engineer to join our teams across Brisbane, Melbourne, and Sydney. You will build and manage automated CI/CD pipelines for ML models, ensure ethical AI practices, and liaise with product managers and business stakeholders to translate requirements into scalable solutions.

The role requires collaboration with data scientists and engineers, keeping up-to-date with evolving ML architectures, and applying ML Ops best practices in a federal

Qualifications

• 3+ years of AI/ML engineering experience with a proven track record.
• Build automated CI/CD pipelines to test, deploy, monitor and retrain models.
• Implement ethical AI practices and assess privacy risks.
• Collaborate with data scientists, engineers and product teams.
• Stay current with new model architectures and ML Ops practices.
• Advanced degree in computer science, statistics, mathematics, or related field with ML focus.

Responsibilities

• Design and implement end-to-end ML pipelines (in production).
• Collaborate with data scientists and engineers on system integration.
• Communicate solution designs with product managers and stakeholders.
• Monitor deployed models and retrain as needed for performance and ethics.

Skills

CI/CD pipelines

Ethical AI

Stakeholder communication

Model architectures

Cross-functional collaboration

Education

Advanced degree in CS/Stats/Math

Job description

One of our Federal Government clients is looking for Senior Machine Learning Ops Engineer in Brisbane, Melbourne and Sydney.

We are looking for the following Skills/Experience:

• Build automated CI/CD pipelines to test, deploy, monitor and retrain models.
• Implement ethical AI practices and assess privacy risks.
• Work with data scientists and engineers on system integration, and with product teams on requirements.
• Communicating solution designs with product managers and business stakeholders.
• Staying current with new model architectures, and evolving MLOps best practices.
• Advanced degree in computer science, statistics, mathematics, or a related field, with a focus on datascience, machine learning, or artificial intelligence.
• Experience (3+ years) in AI/ML engineering with a proven track record.

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