Company Description
Nine is Australia’s largest locally owned media company. Working at Nine, you’ll have access to a unique range of experiences and opportunities, helping drive the success of the country’s most trusted television, radio, digital and publishing brands.
Our content reaches almost every Australian - meaning what we do has real impact. We bring people together, celebrate the big moments, and capture the everyday ones.
Some of our most beloved brands have been part of Australian life for generations, and others - new on the scene - have already found their place firmly in our lives. We’re evolving and we need people like you to bring new ideas, innovate and make your mark.
Job Description
The data science and AI team develops, builds and delivers data science and AI products to provide insights and solutions to business problems. Key responsibilities include gathering and analysing data, developing and implementing data science models or agentic workflows, and communicating findings to stakeholders. We push the envelope in what is possible and work on new and novel implementations of data science techniques.
Areas of focus for the team include implementing generative AI to aid our content creation stakeholders, building recommendation and personalisation solutions and forecasting important metrics to drive data driven decision making.

Day to day you will:

• Lead the architectural design and implementation of robust, scalable MLOps pipelines.
• Drive the technical strategy and development of sophisticated AI agentic systems and Retrieval-Augmented Generation (RAG) pipelines.
• Guide the engineering approach for leveraging Large Language Models (LLMs) and other generative AI technologies to solve business problems.
• Manage, mentor, and lead a high-performing team of Machine Learning and AI Engineers.
• Own the operational integrity and performance of all production machine learning and AI systems, establishing best practices for CI/CD, automated testing, monitoring, and incident response.
• Architect and build the core cloud infrastructure (GCP) for large-scale model training, fine-tuning, and real-time inference.
• Champion a culture of automation, operational excellence, and continuous improvement, ensuring adherence to data privacy, governance, and security standards.

Qualifications

What you’ll bring:

• Bachelor’s degree in Computer Science, Software Engineering, or related field.
• 8+ years in software engineering, with 4+ years in production machine learning systems, including technical leadership or people management.
• Expert-level Python programming for production systems, with demonstrated experience in designing and building LLM applications.
• Strong understanding and hands-on experience with generative AI technologies (RAG, vector databases, embedding models) and MLOps principles and tooling (e.g., Vertex AI, Kubeflow, MLflow).

• Strong proficiency with cloud platforms (preferably GCP), containerization (Docker), and orchestration (Kubernetes).(Desirable) Master’s or PhD in a relevant technical field; proficiency with AI frameworks (LangChain, LlamaIndex), experience with fine-tuning open-source LLMs, familiarity with big data processing (Spark), prior media industry experience, knowledge of multi-modal AI systems, and proficiency with Infrastructure as Code (Terraform).

• Additional Information

Please refer the Job description for details