Job Description
AI/Machine Learning Engineers required in capital cities throughout Australia. You will be responsible for designing, developing, deploying, and maintaining high-performance machine learning models and AI-driven solutions that directly impact business strategy. These roles are critical components in the digital transformation, focusing on production-ready systems that utilise modern cloud data architecture.
MUST HOLD VALID AUSTRAL WORK RIGHTS AND CURRENTLY RESIDE IN AUSTRALIA
Key Responsibilities
Model Development: Design, build, train, and test robust Machine Learning (ML) models (e.g., predictive models, classification, forecasting) using Python and standard ML frameworks.
Production Deployment: Implement models into production using best practices for MLOps, ensuring scalability and reliability on AWS or Azure cloud platforms.
Data Engineering: Work closely with data engineers to access, transform, and manage large-scale datasets stored in Snowflake for model training and inference.
Code Quality: Write clean, well-documented, and efficient Python code, utilising libraries such as Pandas, NumPy, Scikit-learn, and TensorFlow/PyTorch.
Infrastructure: Manage cloud resources for ML workloads, including setting up compute environments, data pipelines, and security protocols on AWS (e.g., SageMaker) or Azure (e.g., Azure ML).
Collaboration: Partner with business stakeholders and product owners to translate complex business problems into viable AI solutions.
Essential Technical Requirements
Machine Learning (ML): Deep experience with model training, validation, MLOps, A/B testing, and strong understanding of deep learning fundamentals.
Programming: Expert-level proficiency in Python is mandatory, including common libraries like Scikit-learn, Pandas, NumPy, and TensorFlow/PyTorch.
Cloud Platforms: Strong deployment experience in either AWS (e.g., S3, EC2, SageMaker) OR Azure (e.g., Azure ML, Azure Data Factory).
Data Warehouse: Proven experience working with data housed in Snowflake, including strong SQL skills for data ingestion and manipulation.
Tools/Other: Experience with Git/GitLab, Docker/Kubernetes, REST API integration, and data visualisation tools.
Qualifications
Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related quantitative field.
Relevant cloud certifications (e.g., AWS Certified Machine Learning Specialist or Azure AI Engineer) are highly advantageous.
If you're ready to bring structure, energy, and precision to a fast-paced project team, we’d love to hear from you.
For more information, please contact Fab on 08 943744***or ***@drdgroup.com.au
DRD Group is a specialist recruitment provider renowned for recruiting quality project teams on major projects within the Energy, Resources, Defence, Renewables and Infrastructure sectors.
DRD Group embraces a diverse workforce culture and encourages applicants from all backgrounds to apply. All work assignments are subject to successful completion of a medical, drug and alcohol screen plus verification of all original certifications and qualifications.
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