Staff Machine Learning Engineer

Job title: Staff Machine Learning Engineer

Company: REA Group


Job description:

• Make an impact shaping the future of AI systems powering REA’s personalisation for consumers!
• Work across a leading property brand impacting millions of users!
• Permanent full time role based in Richmond

We’re REA
With bold and ambitious goals, is changing the way the world experiences property. No matter where you’re at on your property journey, we’re here to help with every step – whether that’s finding or financing your next home.Our people are the key to our success. At the heart of everything we do, is a thriving culture centred around high performance and care. We are purpose driven and collaborative, which drives innovation and our ability to make a real impact. As such, we’re proud to have been named in Australia’s “Top 5” Best Workplaces two years in a row, as well as being recognised as a Best Workplace for Women.Where the team fits in
As a Staff Machine Learning Engineer in the AI Workflows team (part of the Consumer Experience division), you’ll play a key role in shaping the future of REA’s property journey by designing and scaling intelligent AI Assistants that enhance our web and app experiences. You will lead the development of real-time, production-grade AI systems using Generative AI, Large Language Models and Agentic AI architectures. These solutions power smart recommendations, contextual listing insights and conversational support, creating personalised and engaging experiences for millions of users.In this role, you’ll design and guide the implementation of complex AI workflows spanning deep learning, transformers and LLMs, while connecting multiple systems such as recommender engines, search ranking and decision models. You’ll also influence technical direction and mentor engineers in the team to ensure scalability, reliability and innovation in our AI stack. You’ll work closely with teams across Consumer Product, Consumer Experience, Data Services and PropTrack, contributing to REA’s broader AI strategy. Your work will help operationalise cutting-edge research and surface meaningful, context-aware intelligence that empowers users throughout their property journey.What the role is all about

• Design scalable, multi-modal AI solutions (text, image, audio, video) for our web and app platforms.
• Utilize Generative AI, LLMs, and VLMs, combining them with traditional ML techniques to deliver impactful solutions.
• Build and deploy real-time ML, APIs and batch pipelines using multi-cloud frameworks (AWS/GCP) and tools like SageMaker/VertexAI, Docker, Infrastructure as Code, and Python.
• Deliver end-to-end AI products, taking ideas from prototype to production in fast, iterative cycles
• Use state-of-the-art LLMs and Agentic AI frameworks to build smart, goal-driven AI workflows
• Optimise AI pipelines for speed and efficiency using techniques like quantisation, caching, distillation, multi-GPU training, and hybrid approaches that blend GenAI and classical ML
• Evaluate LLM-based solutions consistently in offline and online environments, including A/B testing and performance monitoring
• Extend model capabilities with feedback loops and enable dynamic, incremental learning through integration with knowledge databases and internal data systems
• Build AI orchestrators using techniques like multi-armed bandits and reward models to optimise decision-making in real time
• Collaborate with internal stakeholders to design and enhance data products.
• Promote REA’s AI, ML, and analytics capabilities both internally and externally.
• Support and share knowledge with junior team members.

Who we’re looking for

• MSc or PhD in Computer Science, Computational Physics, Mathematics, Statistics, or a similar discipline.
• Proven commercial experience in ML engineering, data science, or related fields.
• Proficiency in large-scale development with one of the following programming languages: Python or similar language.
• Strong expertise in one or more of the following areas:

• Deep Learning
• Generative AI / Agentic AI
• Prediction Models or Recommender Systems
• Machine Learning
• Experience with key ML libraries such as PyTorch, HF models, Transformers, NLTK, Pandas, LangGraph, AutoGen, Pydantic AI, MCP, LLMs APIs.
• Familiarity with relational databases (e.g., MySQL, PostgreSQL), BigQuery and NoSQL databases (e.g., Redis/DynamoDB, ElasticSearch/Solr, GraphDB).
• Cloud experience with one of the major providers:

• AWS (e.g., EC2, ELB, S3, VPC, Route 53)
• Google Cloud (e.g., Vertex AI, Compute Engine, Pub/Sub, GCS)
• Proficiency with containerisation technologies such as Docker.
• Experience deploying AI systems in real-time, production environments.
• Familiarity with deployment tools like Terraform, or CloudFormation.
• Strong communication and interpersonal skills.

The REA experienceThe physical, mental, emotional and financial health of our people is something we’ll never stop caring about. This is a place to learn and grow.Some of our include:

• A hybrid and flexible approach to working
• Flexible leave options including, birthday leave and purchase additional leave
• Flexible parental leave offering for primary and secondary carers
• Our Because We Care program offers employees volunteering leave, community grants, matched payroll giving and our Community Café donates 100% of revenue to charity
• Hackdays so you can bring your big ideas to life

Our commitment to Diversity, Equity, and InclusionWe are committed to providing a working environment that embraces and values diversity, equity and inclusion. We believe teams with diverse ideas and experiences are more creative, more effective and fuel disruptive thinking. If you’ve got the skills, dedication and enthusiasm to learn but don’t necessarily meet every single point on the job description, please still get in touch.Join our Talent NeighbourhoodKeen to be part of REA but didn’t find a perfect match with this opportunity? Perhaps the timing isn’t right?#LI-HYBRID

Expected salary:

Location: Richmond, VIC – Melbourne, VIC

Job date: Wed, 20 Aug 2025 00:57:51 GMT

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