ML Engineer
MelbourneOn-siteFull-time
AI Summary
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 fast-moving engineering team with real ownership, shipping to production daily and using AI as part of how we work.
About this role
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 fast-moving engineering team with real ownership, shipping to production daily and using AI as part of how we work.
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.
What you'll do:
What you'll need:
- Strong Python Skills: Commercial experience building machine learning applications and data pipelines using Python and relevant machine learning libraries.
- Machine Learning Expertise: Hands on experience developing, evaluating and deploying machine learning models in production environments.
- MLOps Experience: Experience building and maintaining model deployment, monitoring and retraining pipelines using modern MLOps practices and tools.
- Data Engineering Foundations: Strong SQL skills and experience working with large datasets, feature engineering workflows and distributed data processing systems.
- Cloud Experience: Hands on experience with cloud platforms, preferably Google Cloud Platform (GCP), including Vertex AI, BigQuery and Cloud Run.
- Software Engineering Best Practices: Strong understanding of Git, CI/CD, testing frameworks, containerisation and production system reliability.
- AI & LLM Experience: Experience working with LLMs, embeddings, vector databases, RAG architectures or AI agents through commercial or personal projects.
- Problem Solving Mindset: A practical engineering approach that balances experimentation and innovation with reliability, scalability and business impact.
- Recommendation & Forecasting Systems: Experience building recommendation systems, search ranking models or forecasting solutions.
- ML Platforms & Tooling: Exposure to ML platforms and tools such as Vertex AI, Databricks, SageMaker or Kubeflow.
- Streaming & Event Driven Systems: Experience with event driven architectures and streaming technologies such as Kafka or Pub/Sub.
- LLM Application Deployment: Experience deploying AI applications powered by LLMs and agent frameworks.
Bonus Points
Why Kogan.com?
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