DescriptionSenior AI / ML / Agent Engineer to join a Azure Quantum programme — a hands-on builder role at the intersection of agentic AI, applied machine learning, and quantum-inspired computing.
You'll work alongside quantum specialists, data engineers, and domain experts to take high-value use cases from problem framing through to working solution.This is a build role, not an advisory one. You'll be writing code daily — building agents, training and tuning models, integrating with Azure Quantum and quantum-inspired optimisation services, and standing up the AI/ML scaffolding that surrounds the quantum workloads. Expect ambiguity, fast iteration, and the need to make pragmatic calls about when to use a classical model, when to reach for an agentic pattern, and when quantum or QIO is the right tool.Key responsibilitiesDesign and build agentic systems on Azure AI Foundry / Semantic Kernel — including orchestration, tool use, memory, and evaluationDevelop, train, and deploy machine learning models supporting quantum and quantum-inspired use cases (optimisation, simulation, materials, logistics)Integrate AI/ML components with Azure Quantum workloads, quantum-inspired optimisation (QIO) services, and classical Azure computeBuild data pipelines and feature engineering workflows in partnership with the Fabric data engineerImplement evaluation frameworks for both ML models and agent behaviours — including safety, accuracy, and cost metricsProductionise experimental work — move from notebook to deployed service with appropriate testing, monitoring,



and CI/CDPartner with BHP domain experts to translate operational problems into AI/ML and quantum-suitable formulationsContribute to architectural decisions across the AI/ML/quantum stackRequirementsExperience
7+ years building and deploying ML systems in production environmentsDemonstrated hands-on experience building agentic systems — Azure AI Foundry, Semantic Kernel, LangChain, AutoGen, or equivalentProduction experience with LLMs — RAG, fine-tuning, prompt engineering, evaluation, and guardrailsTrack record of taking ML work from prototype to production, including MLOps practicesExperience in resources, mining, or heavy industry highly regarded but not required
Technical skills — must-have
Robust Python — daily working language, including ML libraries (PyTorch or TensorFlow, scikit-learn, NumPy, pandas)Hands-on experience with Azure AI services — Azure AI Foundry, Azure OpenAI, Azure ML, or equivalentDemonstrated ability to build, evaluate, and deploy AI agents — not just call an LLM APISolid software engineering fundamentals — Git, testing, CI/CD, containerisation (Docker), API designComfortable with SQL and modern data tooling (Fabric, Synapse, Databricks, or similar)




Technical skills — highly regarded
Azure Quantum, Q#, or quantum-inspired optimisation (QIO) experienceOptimisation and operations research background — linear programming, combinatorial optimisation, constraint solversMaterials science, computational chemistry, or simulation experienceReinforcement learning, particularly for control or optimisation problemsExperience with vector databases and retrieval systems (Azure AI Search, pgvector, Pinecone, etc.)
Engineering practice
Writes clean, maintainable, tested code — not just notebooksComfortable working across the stack — data, models, agents, deployment, monitoringStrong evaluation discipline — measures before claiming, knows the difference between a demo and a system that worksBias to shipping — moves from problem to working code quickly without skipping the basics
Qualifications
Tertiary qualification in Computer Science, Engineering, Mathematics, Physics, or related STEM disciplinePostgraduate qualifications in ML, AI, optimisation, or quantum computing — strong advantageMicrosoft certifications (AI-102, AZ-900 minimum) — advantage
Attributes
Comfortable with ambiguity and fast learning curvesPragmatic about tooling — uses the right approach for the problem, not the one that's trendyStrong written communication — can explain technical work to both engineers and business stakeholdersCollaborative — works well with quantum specialists, data engineers, and domain experts

📌 Senior AI/ML/Agent Engineer (Perth)
🏢 SG Consulting
📍 Perth