ML Engineer

Kogan.com is seeking an ML Engineer to design and run data and ML pipelines that support teams across Marketing, Purchasing, Logistics, and Finance. The role involves building and deploying machine learning models, MLOps pipelines, and LLM-powered applications in a fast-moving, AI-native engineering environment. Strong Python, machine learning, MLOps, data engineering, and cloud (preferably GCP) experience are required.

Core AIOn-siteFull-timeEntry LevelPythonMachine Learning

ML Engineer

Kogan.com is seeking an ML Engineer to design and run data and ML pipelines that support teams across Marketing, Purchasing, Logistics, and Finance. The role involves building and deploying machine learning models, MLOps pipelines, and LLM-powered applications in a fast-moving, AI-native engineering environment. Strong Python, machine learning, MLOps, data engineering, and cloud (preferably GCP) experience are required.

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Core AIOn-siteFull-timeEntry LevelPython

Salary

Not specified

Work Location

South Melbourne, Victoria, Australia, AU

Work Model

On-site

Employment Type

Full-time

Experience Level

Not Applicable

Core Qualifications

Technical (Must-have)

PythonMachine LearningMLOpsSQLGoogle Cloud Platform (GCP)Vertex AIBigQueryCloud RunGitCI/CDContainerisationLLMsEmbeddingsVector DatabasesRAG Architectures

Soft Skills

Problem SolvingCross Functional CollaborationPractical Engineering Mindset

Preferred Qualifications

Technical (Nice-to-have)

Recommendation SystemsSearch Ranking ModelsForecasting SolutionsDatabricksSageMakerKubeflowApache KafkaPub/SubAgent Frameworks

Key Responsibilities

•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
•Build reliable and scalable machine learning services that deliver predictions in both real time and batch environments, ensuring strong performance, reliability and cost efficiency
•Develop and maintain MLOps pipelines that automate model training, validation, deployment, monitoring and retraining
•Work with large datasets to create robust feature pipelines and reusable datasets that improve model performance and accelerate experimentation
•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
•Implement monitoring frameworks to track model performance, drift, accuracy and business impact, continuously improving models in production
•Partner with Product Managers, Engineers, Analysts and business stakeholders to identify opportunities where machine learning can create measurable value
•Develop solutions in line with software engineering best practices, including Git, CI/CD, trunk based development, testing and observability
•Contribute to experiments with AI and emerging technologies, helping shape how Kogan.com leverages machine learning and automation across the business

ML EngineerRetaileCommerceMachine LearningMLOpsPythonGCPLLMFull-timeOn-site