Job Description

ML/AI Specialist

12 Month Contract with a 12 Month extension 

Hybrid Working Style 

Qld State Gov 

Brisbane City 

Position Overview
The ML/AI Specialist will design, develop, and deliver machine learning and artificial intelligence solutions and provide strategic guidance on policy and frameworks as part of an enterprise GenAI Adoption Program. The role will progress Statements of Need through rapid Proofs of Concept (PoCs), pilots, and preparation for production—ensuring compliance with government enterprise architecture, information security, privacy, and responsible AI principles while providing operational readiness insights for handover to BAU/operations. The position contributes to program governance by producing clear technical evidence to support adoption decisions.

Key Responsibilities

Solution Development

• Build and evaluate ML models and GenAI solutions including LLMs and RAG pipelines
• Integrate enterprise-approved AI services and orchestrate LLM/RAG components to augment business processes
• Implement prompt engineering techniques and safety filters to ensure responsible use

Data Engineering

• Prepare, transform, and curate datasets to ensure quality and compliance with privacy legislation
• Align data handling with organisational classification and security expectations
• Leverage existing enterprise data pipelines and products where appropriate

Deployment & Automation

• Package PoCs for pilot environments and collaborate with MLOps on CI/CD pipelines
• Develop operational readiness artefacts including observability baselines, SLO proposals, and incident scenarios
• Provide change and release inputs to support transition to operations

Governance & Compliance

• Prepare model summaries, evaluation reports, and risk mitigation documentation
• Support program stage-gates and governance forums
• Align solutions with protective security, data sovereignty, and relevant government guidance

Strategic Policy & Framework Guidance

• Provide expert input to policy owners on updates to AI governance frameworks
• Contribute to assessment processes aligned with State/Federal guidance and industry practice

Collaboration & Capability Uplift

• Work within cross-functional squads to advise on feasibility and solution design
• Participate in governance reviews and workshops
• Produce reference implementations and concise guidance to embed lessons learned

Capabilities / Desirable Attributes

1. AI/ML Engineering, LLMs, RAG & Data

• Strong Python skills (pandas, scikit-learn)
• Experience with LLM orchestration, retrieval patterns, and prompt engineering
• Familiarity with embeddings, vector databases, and RAG architectures
• Data preprocessing, feature engineering, and model evaluation

2. Cloud, MLOps & DevOps

• Experience with cloud platforms (Azure preferred)
• Exposure to AI/ML services, data platforms, and search technologies
• GitHub/Azure DevOps, CI/CD, and containerisation (Docker)
• Relevant Azure AI/ML certifications desirable

3. Security, Privacy & Responsible AI

• Understanding of privacy-by-design and responsible AI principles
• Knowledge of security controls such as encryption and access management
• Ability to explain complex AI concepts to non-technical stakeholders
• Agile mindset with rapid prototyping experience

Mandatory Requirements

• Degree in Computer Science, Data Science, AI/ML, or related discipline

SFIA 9 Alignment

• Machine Learning (MLNG) – Level 5: Leads design, training, tuning, and evaluation of models
• Programming/Software Development (PROG) – Level 5: Leads design, coding, testing, documentation
• Cloud Computing (CLCO) – Level 4: Implements and operates cloud services
• Information Security (SCTY) – Level 4: Applies and maintains security controls
• Consultancy (CNSL) – Level 4: Provides technical advice and stakeholder engagement
• Information Assurance (INAS) – Level 5: Ensures governance and risk compliance

Key Selection Criteria

Candidates will be assessed on:

1. Demonstrated experience performing the key responsibilities
2. Evidence of desirable capabilities
3. Meeting all mandatory requirements
4. Strong written and oral communication skills
5. Availability to commence at the required start date

Work Model
Flexible resource model – the successful candidate may be assigned across similar projects and initiatives to support organisational priorities.

Application Notes
Applicants should provide a CV and response addressing the key selection criteria, highlighting experience with GenAI, RAG, cloud AI platforms, governance, and production readiness.