Machine Learning Engineer

One of our Federal Government Clients is seeking to engage a Senior Machine Learning Ops Engineer. This is a long-term contractual position.

Please check below all the job details:

Contract Duration: 03 Years (12 months initially + 24 months extension)

Work Location : Brisbane, Melbourne, Sydney (03 Days office/02 Days home per week)

Eligibility: You must need to have Baseline Security Clearance or above.

Position Description:

Mandatory Skills & Experience

• Data engineering: Level 5 (SFIA) – Plans and drives the development of data engineering solutions ensuring that solutions balance functional and non-functional requirements . Monitors application of data standards and architectures including security and compliance . Contributes to organisational policies, standards, and guidelines for data engineering.
• Machine learning: Level 4 (SFIA) – Given a well-described problem and dataset, assesses whether machine learning is likely to provide an effective solution . Implements algorithms developed by others . Advises on the effectiveness of specific techniques , based on project findings and wider research. Contributes to the development, evaluation, monitoring and deployment of machine learning systems . Understands and applies rules and guidelines specific to the industry, and anticipates risks and other implications of modelling .
• Release and deployment: Level 5 (SFIA) – Leads the assessment, analysis, planning and design of release packages , including assessment of risk . Liaises with business and technology teams on release scheduling and communication of progress. Conducts post-release reviews . Ensures that release processes and procedures are applied and that releases can be rolled back as needed. Identifies, evaluates and manages the adoption of appropriate release and deployment techniques, processes and automation tools .
• Experience (3+ years) in AI/ML engineering with a proven track record

Niche/core experience to target:

• 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.
• Implements algorithms and AI developed by Data Scientists.
• 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.