The safety and wellbeing of our employees and potential employees are important to us. All external candidates will be interviewed over Zoom and we will not be conducting any face-to-face interviews in any of REA’s Australian offices – with no exceptions. The reasons for this are not only to protect the health and safety of our people, but also to assure candidates that there is no expectation from REA to meet face-to-face. A virtual interview will not adversely impact your application. If you have any questions or concerns, this can be discussed through the screening process.
An Australian start-up success story we’re quietly proud of.
From a garage in Melbourne to the global stage is an achievement we’re humbled by. Our idea to put pictures of houses on the internet has blossomed since 1995, and we now have businesses across Australia, Asia, India and North America.
Our purpose is to change the way the world experiences property. No matter where you’re at on your property journey, we’re here to help on every step – whether that’s buying, selling, renting or renovating.
Some of our brands include realestate.com.au, realcommercial.com.au, spacely.com.au, Flatmates.com.au, smartline.com.au and hometrack.com.au.
What we’re doing
With us, you’ll experience Complexity. The Machine Learning Engineer role sits in the Property Data (aka “The Castle”) team in the Data Services Tribe within the Technology and Data Group, headed up by Tom Varsavsky.
The Data Services Tribe supports and develops data flows, data storage and property data insights which underpin REA’s revenue and product growth.
Our mission is to:
- Improve the quality, access and usage of our data for consumers, and customers.
- Build reusable data products and patterns that unlock value stored in our data
- Create unique insights based on user, listings and customer data
- Invest in the reliability, quality and security of systems and data
This position plays a pivotal role in helping REA to become the market leader in property data and supporting REA’s FY20 OKR’s to be the #1 source of property Insights for Consumers, Customers and the Media. The key to this is uplifting our pipelines to provide the most accurate, comprehensive, and timely property data in the Australian market.
What you’ll be doing
As a Machine Learning Engineer, you will support the Castle and Data Science teams in the following ways:
- Designing, coding, testing, and deploying new Machine Learning pipelines using Airflow, Python, SQL, and other technologies
- Support the Data Science to implement new Machine Learning pipelines
- Support data processes - assist with ad-hoc analysis, automated dashboards, and self-service reporting tools so that everyone gets a good sense of the state our data
- Identify, track, and remediate data quality issues as well as perform exception handling across a broad variety of data sets
- Support data processes - provide the team with ad-hoc analysis, automated dashboards, and self-service reporting tools so that everyone gets a good sense of the state our data
- Analyse and produce data coverage and quality statistics across internal and external data sets to provide a high level of awareness across multiple teams
- Champion quality software delivery from inception and design to build and deployment, in collaboration with our Lead Developer and Technical Lead
- Following agile software development practices such as test-driven development, continuous delivery and pair programming.
- Sharing responsibility for all operational aspects of the software that we build, in support of our “you build it; you run it” philosophy where dev-ops is a part of everyday life.
- Learning – we are constantly learning together, mentoring each other and striving to do things better
- Working with product managers to understand business priorities and communicate technical options, report on progress and express ideas
Who we’re looking for
Our ideal candidate will have skills in the following areas:
- Programming skills. This can be SQL, Python, R, C#, or anything else. We’re happy for you to learn the particulars on the job, but you need to be able to code.
- Experience with devops tools and techniques, particularly AWS, CloudFormation, Terraform, GCP, and Docker
- Experience with building and running Computer Vision Machine Learning models
- Experience with designing and automating Machine Learning pipelines
- Experience with modern software development techniques such as test-driven development, microservice architecture and continuous delivery.
- Able to communicate and collaborate effectively with business stakeholders
- Ability to manage the competing demands of multiple projects in a timely manner – #gsd
- Good communication skills and experience collaborating with other team members
- A track record of delivering software to high quality standards, deploying and supporting the software that you deliver right through to production (past AWS or GCP experience a bonus).
- Exposure to agile software engineering practices with a passion for continuous improvement
But we don’t just look for someone based on their skills and expertise. It’s our connection, acceptance and genuine care for each other that makes REA a great place to work. That means you also need to be:
- Savvy minded and have the ability to think a little left of field / outside the box
- A strong and creative communicator
- Friendly, approachable and have good relationship management skills
- An avid supporter of our fully inclusive culture - we celebrate difference and ensure that everyone belongs
The REA experience
The 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. We’re committed to your development – both professionally and personally. Your experience with us is something we take seriously.
- Because We Care program which includes volunteer leave and community grants, to ensure you have the opportunity to give back to your community
- Hack Days so you can bring your big ideas to life
- An additional day of leave just for your birthday
- A flexible working environment meaning we strike the balance of what you need and what works for the business (and yes, our leaders fully understand the flexible working policy)
- Free breakfast (and who doesn’t love a free brekkie)
- Industry leading gender-neutral parental leave
If you like the sound of us, then we think you should apply today. While we take a look at your application, we encourage you to get to know us a bit more through our various social channels.