One of our Federal Government Clients is seeking to engage a Senior Machine Learning Ops Engineer – EL1

Please check below all the job details:

1. Contract Duration: 03 Years (12 Months initially + 24 Months extension)
2. Work Location: Brisbane, Melbourne and Sydney (Hybrid available)
3. Work Arrangement: First 6 weeks work fulltime onsite, thereafter work 3 days from office and 2 days from home each week
4. Eligibility: You must need to have Baseline Security Clearance or above.
5. Tentative Start Date: 1st Dec 2026
6. Working Hours: 8 hours a day/ 40 hours a week

Overview ML Ops Engineers are involved in setting the overall ML Ops strategy for the organisation as well as the management of complex projects. They will work closely with cross-functional teams including data scientists, engineers and business stakeholders to ensure that ML Ops initiatives are aligned with industry standards and business goals.

The role of a Machine Learning OPs Engineer includes:

1. Plans and drives the development of data engineering solutions ensuring that solutions balance functional and non-functional requirements.
2. Monitors application of data standards and architectures including security and compliance.
3. Contributes to organisational policies, standards, and guidelines for data engineering. Given a well-described problem, assesses whether machine learning is likely to provide an effective solution.
4. Implements algorithms and AI developed by Data Scientists.
5. Advises on the effectiveness of specific techniques, based on project findings and wider research.
6. Contributes to the development, evaluation, monitoring and deployment of machine learning systems.
7. Understands and applies rules and guidelines specific to the industry and anticipates risks and other implications of modelling. Leads the assessment, analysis,



planning and design of release packages, including assessment of risk.
8. Liaises with business and technology teams on release scheduling and communication of progress.
9. Conducts post-release reviews.
10. Ensures that release processes and procedures are applied and that releases can be rolled back as needed.
11. Identifies, evaluates and manages the adoption of appropriate release and deployment techniques, processes and automation tools.

Key duties and responsibilities:

1. Build automated CI/CD pipelines to test, deploy, monitor and retrain models.
2. Implement ethical AI practices and assess privacy risks.
3. Work with data scientists and engineers on system integration, and with product teams on requirements.
4. Communicating solution designs with product managers and business stakeholders.
5. Staying current with recent model architectures, and evolving MLOPs best practices.

Knowledge / Qualifications:

1. Advanced degree in computer science, statistics, mathematics, or a related field, with a focus on data.
2. Science, machine learning, or artificial intelligence.
3. Experience (3+ years) in AI/ML engineering with a proven track record.

Technical skills:

- Git.
- Build batch and streaming data pipelines.
- Implement data solutions with RDMS databases, distributed file systems and blob storage.
- SQL and Spark/pyspark.
- Python API and ML Frameworks.
- Containerization.
- Use of mlflow, Kubeflow or equivalent.
- Linux skills.
- Kubernetes (Red Hat openshift preferable).
- Relational databases.
- Python.
- Data Lakes (Hadoop, Hive, Impala, Kafka).

The Next step is easy: If you are interested, you may send an email to [email protected] Referral incentive program: As always, we have the candidate referral incentive program through which you will get $1000 for each successful referral after the successful selection and joining of the referred candidates

📌 Senior Machine Learning Ops Engineer (Australia)
🏢 IT Alliance Australia
📍 Australia