Job Description
/n /n /n /n Kogan.com is a pioneer of Australian eCommerce, and the software we build is used by millions of customers every day. You'll join a rapid-moving engineering team with real ownership, shipping to production daily and using AI as part of how we work./n /n /n /n /n /n As a Data Engineer you'll design and run the data and ML pipelines that let teams across Marketing, Purchasing, Logistics and Finance make confident, data-driven decisions./n /n /n /n /n

What you'll do
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- Machine Learning Development: Design, build and deploy machine learning models that solve practical business problems, including recommendation systems, demand forecasting, customer segmentation, churn prediction, pricing optimisation and fraud detection. /n
- Production ML Systems: Build reliable and scalable machine learning services that deliver predictions in both real time and batch environments, ensuring strong performance, reliability and cost efficiency. /n
- MLOps & Automation: Develop and maintain MLOps pipelines that automate model training, validation, deployment, monitoring and retraining. /n
- Feature Engineering: Work with large datasets to create robust feature pipelines and reusable datasets that improve model performance and accelerate experimentation. /n
- LLM & Generative AI Applications: Design, evaluate and deploy AI powered solutions using large language models (LLMs), retrieval systems, agents and emerging AI technologies to enhance customer experiences and internal productivity. /n
- Model Monitoring & Optimisation: Implement monitoring frameworks to track model performance, drift, accuracy and business impact, continuously improving models in production. /n
- Cross Functional Collaboration: Partner with Product Managers, Engineers,



Analysts and business stakeholders to identify opportunities where machine learning can create measurable value. /n
- Software Engineering Excellence: Develop solutions in line with software engineering best practices, including Git, CI/CD, trunk based development, testing and observability. /n
- AI Collaboration: Contribute to experiments with AI and emerging technologies, helping shape how Kogan.com leverages machine learning and automation across the business. /n /n /n /n /n /n /n /n /n

What you'll need
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- Strong Python

Skills:
Commercial experience building machine learning applications and data pipelines using Python and relevant machine learning libraries. /n
- Machine Learning Expertise: Hands on experience developing, evaluating and deploying machine learning models in production environments. /n
- MLOps

Experience:
Experience building and maintaining model deployment, monitoring and retraining pipelines using modern MLOps practices and tools. /n
- Data Engineering Foundations: Strong SQL skills and experience working with large datasets, feature engineering workflows and distributed data processing systems. /n
- Cloud

Experience:
Hands on experience with cloud platforms, preferably Google Cloud Platform (GCP), including Vertex AI, BigQuery and Cloud Run. /n
- Software Engineering Best Practices: Strong understanding of Git, CI/CD, testing frameworks, containerisation and production system reliability. /n
- AI & LLM





Experience:
Experience working with LLMs, embeddings, vector databases, RAG architectures or AI agents through commercial or personal projects. /n
- Problem Solving Mindset: A practical engineering approach that balances experimentation and innovation with reliability, scalability and business impact. /n Bonus Points/n /n
- Recommendation & Forecasting Systems: Experience building recommendation systems, search ranking models or forecasting solutions. /n
- ML Platforms & Tooling: Exposure to ML platforms and tools such as Vertex AI, Databricks, SageMaker or Kubeflow. /n
- Streaming & Event Driven Systems: Experience with event driven architectures and streaming technologies such as Kafka or Pub/Sub. /n
- LLM Application Deployment: Experience deploying AI applications powered by LLMs and agent frameworks. /n /n /n /n /n /n /n /n /n Why Kogan.com?/n /n /n /n
- AI-Native Engineering: AI is deeply embedded in how our Engineering teams build and operate. We’re moving beyond standalone LLM use into agentic workflows, AI-assisted development and automation integrated into real engineering systems and processes. Engineers have access to leading AI tools, hands-on training and the freedom to experiment with new ways of designing, building and shipping software. /n
- Our culture is unlike anywhere else and regardless of where you are in your career journey, we empower you to do your best work and have a big impact. Check us out https://devblog.kogan.com/ & https://goodteams.app/teams/kogan.com. /n
- Work with an incredible team to solve key challenges, helping to drive Australia and New Zealand's eCommerce future. /n
- Your role has a lot of ownership, autonomy and little red tape. You'll be empowered to achieve

📌 ML Engineer (Melbourne)
🏢 Kogan.com
📍 Melbourne