Which team is this in The AI Enrichment squad sits within the Property & Future of Search portfolio , part of the broader Consumer Product group, headed up by our Executive General Manager. We are creating new products and solutions that will impact how Australians experience property, today and into the future. Day to day you'll be working with a multifunctional team across product, ML, engineering, data, and consumer experience. You'll be working with a collaborative environment to align around our consumer and team objectives , building systems that leverage ML and/or Generative AI, advocating for innovative ideas, processes and features that deliver on . Day to day of the job This is a unique opportunity to design and deliver delightful and reliable ML products at REA . As our Senior Machine Learning Engineer , you will be instrumental in designing and implementing the intelligent core of our platform. You'll tackle complex challenges in n atural l anguage u nderstanding (NLU), recommendation and ranking systems, semantic search, large language models, and personalization, directly impacting millions of users by helping them discover properties in ways they never thought possible. If you're passionate about using AI to solve real-world problems and want to redefine an entire industry, this role is for you. What the role is all about : Design ing , implementing , test ing , evaluating, deploy ing and observing ML products pipelines /services using Python, ML frameworks (e.g. pytorch ), cloud-native technologies (AWS), devops ( Docker , infrastructure as code, terraform) , data engineering technologies ( Airflow, kafka , SQL, BigQuery ) , and other technologies. Apply engineering best practices (e.g. test automation, CI/CD, refactoring, observability, etc.) to build and operate reliable ML products . Establishing automated evaluation and monitoring systems to track AI products / features performance, detect drift, and ensure quality at scale. Implementing and optimi s ing ML models for ranking, relevance, and retrieval using embeddings, transformers, and LLMs in production environments , measuring and o ptimising 3rd party models . Developing robust data pipelines and feature stores to support real-time and batch inference across various ML product use cases . Owning model lifecycle management including versioning, deployment, and CI/CD integration for reproducible experimentation and delivery. Contributing to discussions, design and delivery of ML platform capabilities to accelerate delivery. Primary languages: Python, SQL . What we’re looking for Proficiency with ML, ML engineering, MLOps , software engineering and LLMs in a commercial production environment Demonstrated knowledge and application of machine learning, statistical analysis and modelling on both structured and unstructured data ( eg image and text). Proficiency in Python, SQL, and/or other relevant ML technologies . We’re happy for you to learn the particulars on the job, but you need to be able to design and create good quality software. Can proactively identify the most appropriate machine learning approach and tools to derive insights for a given commercial application or opportunity. Clear c ommunicat ion and collaboratively work across teams and with various business stakeholders. Ability to both independently and collaboratively lead the design, scoping and delivery of key feature slices to a high quality and to the agreed timelines. Motivation to learn – we are constantly learning together, mentoring each other and striving to do things better. Thrives in a fast-paced environment and willing to adapt quickly .
