At 4WD Supacentre, home of Adventure Kings, we’re one of Australia’s fastest-growing adventure and outdoor retailers — and we’re investing in the next generation of our data and AI capability.
We’re looking for an experienced Data Engineer – AI/ML to help build the data and machine-learning solutions that will drive smarter decisions across forecasting, inventory, ecommerce, marketing and supply chain.
This is a hands-on technical role where you’ll work across the complete ML lifecycle — from feature engineering and model development through to deployment, monitoring and measurable business outcomes.
Location: Sydney Olympic Park, NSW Employment: Permanent | Full-Time Work Arrangement: On-site, 5 days per week Parking: Provided
This isn’t AI for the sake of AI. You’ll work on real commercial problems that directly influence how we operate our stores, ecommerce business and distribution network.
Your initial projects will include:
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Demand forecasting – predicting product, store, seasonal and peak-period demand
- Inventory optimisation – improving stock allocation and reducing stock-outs and excess inventory
- Promotion forecasting – predicting demand uplift before campaigns launch
- Marketing attribution – understanding which campaigns and products drive incremental sales
- Store clustering – identifying stores with similar demand patterns
- Seasonal forecasting – understanding Australian seasonal and holiday demand
- Website demand signals – using search, product views, cart activity and conversion as leading indicators
- Inventory risk prediction – identifying potential stock-outs, excess stock and slow-moving products
- New-product forecasting – predicting demand where limited historical sales data exists
You’ll work closely with our Technology, Data, Ecommerce, Marketing, Merchandise, Supply Chain, Inventory and Operations teams to turn complex business problems into practical AI/ML solutions.
You’ll be responsible for:
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Building scalable data pipelines and ML-ready datasets
- Developing feature engineering pipelines using retail, ecommerce and operational data
- Building, training and tuning machine-learning models
- Performing model validation, backtesting and cross-validation
- Deploying models into production
- Monitoring forecast accuracy and model performance
- Identifying data and model drift
- Building automated testing and data-quality controls
- Integrating multiple business systems and data sources
- Continuously improving model accuracy and commercial performance
Our AI/ML environment is built around Google Cloud, including:
BigQuery | Vertex AI | Cloud Storage | Dataflow | Pub/Sub | Cloud Run | Cloud Functions | Google Cloud Logging & Monitoring | IAM | Secret Manager
Strong experience with BigQuery and Vertex AI will be particularly valuable. You don’t need to have worked with every Google Cloud service, but you should be comfortable designing and supporting production AI/ML solutions in a cloud environment.
As our AI capability continues to develop, you may also have the opportunity to work across:
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Generative AI and LLM applications
- Autonomous and multi-agent systems
- Agentic RAG, Self-RAG and GraphRAG
- LangChain and LangGraph
- CrewAI and AutoGen
- MCP
- AI evaluation
- Human-in-the-loop workflows
We’re particularly interested in engineers who understand when traditional ML is the right solution, when Generative AI adds value and when an Agentic AI architecture genuinely makes sense for the business.
You’re technically strong, commercially aware and someone who takes ownership.
When you’re given a messy dataset or a difficult business problem, you don’t wait for someone else to tell you exactly what to do. You investigate, test, prototype and find a practical way forward.
You’re equally comfortable getting into the technical detail and explaining the commercial impact to stakeholders.
Most importantly, you have a bias towards action — you take ownership, solve problems and get things done.
- 5+ years' experience in Data Engineering, ML Engineering, AI Engineering or a related discipline
- Strong Python and SQL skills
- Hands-on machine-learning experience
- Forecasting or predictive analytics experience
- Feature engineering experience
- Experience training, tuning and evaluating ML models
- Experience taking ML models into production
- Understanding of model monitoring and drift
- Experience working with large and complex datasets
- Experience integrating multiple business systems and data sources
- API and cloud data-platform experience
- Strong understanding of data quality and validation
- Strong analytical and problem-solving capability
- Ability to communicate with technical and non-technical stakeholders
- Agile, Scrum or hybrid delivery experience
- Relevant Bachelor's degree
Experience with GCP, Vertex AI, time-series forecasting, demand forecasting, inventory optimisation, recommendation systems, clustering, BigQuery ML, MLOps, retail/ecommerce data, SAP, Salesforce, Shopify, Magento, Generative AI, RAG or Agentic AI will be highly regarded.
You’ll have the opportunity to help build our AI/ML capability rather than simply maintain an established environment.
You’ll get:
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Competitive remuneration
- Ownership of meaningful Google Cloud AI/ML projects
- Real-world projects with measurable commercial impact
- Exposure to large retail, ecommerce, inventory and supply-chain datasets
- Opportunity to influence how AI is used across the business
- Exposure to modern Generative and Agentic AI
- Adventure Kings employee discounts
- On-site role at Sydney Olympic Park
- Parking provided
If you’re an experienced Data Engineer / AI/ML Engineer who enjoys solving difficult problems, building production solutions and seeing your work make a genuine commercial impact, we’d love to hear from you.
Apply now and help build the intelligence behind the next stage of 4WD Supacentre’s growth.
4WD Supacentre is one of Australia's leading and fastest growing omni-channel retailers. We are a family-operated business that specialises in outdoor recreation and lifestyle products. Our people are passionate about the outdoors and the lifestyle that we can bring to our customers and the community.
