Design and implement scalable AI solutions that enable data engineers and ML scientists to train, build, and maintain machine learning models effectively.
Develop automated processes for continuous model training and evaluation pipelines specifically for ML applications.
Ensure the seamless integration of ANZ Plus’s current architecture with newly added ML functionalities, enhancing overall system capabilities.
Collaborating with diverse stakeholders including business partners, risk, legal, and security teams, as well as UX designers and architects to define and implement robust validation and verification strategies
Fostering a culture of quality coding practices, including test-driven development, unit testing, and secure coding awareness
Focus on business practicality and the 80/20 rule, aiming for the high bar for code quality, but recognize the business benefit of “having something now” vs “perfection sometime in the future”
Requirements & Skills:
Proficiency in one of the scripting/programming languages (Python or Go).
Experience in building software using GCP technologies.
Experience with containerization, Terraform, and GitOps principles for automation and deployment.
Strong background in ML concepts and applications and in-depth knowledge of MLOps best practices.
Agile development mindset, appreciating the benefit of constant iteration and improvement
Have experience of addressing Tech Debt with minimizing production incidents
Familiarity with RAG architectures and/or a good understanding of their application
