AI Engineer

The data science team develops builds and delivers data science products to provide insights and solutions to business problems. Key responsibilities include gathering and analyzing data developing and implementing data science models 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:

• Building and managing scalable machine learning pipelines for various stages from training to deployment.
• Working with data scientists to move models from development to production environments.
• Developing and managing CI/CD and continuous training workflows for ML models.
• Implementing monitoring for production models and optimizing them for performance scalability and cost.
• Working with data and platform engineers to ensure data quality and build efficient data pipelines for AI/ML.
• Continuously learning and applying the latest industry best practices.
• Championing best practices within the data science team including code quality and testing.
• Contributing to a collaborative culture through knowledge sharing and mentorship.
• Adhering to data privacy regulations and ethical standards for all machine learning systems.
   

Qualifications :

What youll bring:

• Minimum of 3 years of commercial experience in a Machine Learning Engineer MLOps or related software engineering role.
• Strong proficiency in Python and a solid understanding of software engineering principles including data structures algorithms and object-oriented design.
• Hands-on experience with cloud platforms (preferably GCP or AWS) and MLOps tools/frameworks for model deployment monitoring and lifecycle management (e.g. Kubeflow MLflow Vertex AI).
• Proficiency with containerization technologies (Docker Kubernetes) and strong SQL skills with experience in large-scale data processing systems.
• Experience with big data technologies (BigQuery Spark) and familiarity with ML libraries/frameworks (Scikit-learn TensorFlow PyTorch).
• Proven experience in designing and building CI/CD pipelines for automated testing and deployment along with a deep understanding of the full lifecycle of data science projects.
• Bachelors degree in Computer Science Engineering or a related technical field is essential with a Masters or PhD being desirable.

Additional Information :

How we work

At Nine our flexible work options vary by role and team. Depending on the position this may include flexible hours hybrid work or part-time arrangements. We welcome discussing your flexibility needs during the hiring process - just ask the Talent Acquisition team. 

Our employee benefits include:

• 18 weeks paid parental leave with no distinction between primary and secondary carers.
• Access to Employee Exclusives program - a way of getting closer to our incredible brands offering unique experiences behind-the-scenes access and awesome perks.
• Digital newspaper subscription to our mastheads.
• Annual gift voucher for Stan subscription.

More info at Nine Careers.

Our Commitment to Diversity and Inclusion:

Were committed to a safe respectful and inclusive Nine. From day one youll be encouraged to bring your whole self to work and will be supported to perform at your best.

We encourage applications from Aboriginal and Torres Strait Islander people people with disabilities and of all ages genders nationalities backgrounds and cultures as we recognise the importance and value of diverse perspectives. Should you require any adjustments to the recruitment process please advise us when you apply.

Work rights: Please note to apply for this role you must already have the right to lawfully work and live in Australia.

Remote Work :

No

Employment Type :

Full-time