1 day ago

Staff Software Engineer - Machine Learning

REA Group

Richmond

1 day ago

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REA Group is seeking a Staff Software Engineer - Machine Learning to shape the intelligent core of its platform and deliver high-value, reliable AI/ML products at scale. The role involves leading strategically important AI/ML initiatives, designing and operating end-to-end ML products, and collaborating across teams. Based in Melbourne or Sydney, this permanent full-time on-site position requires deep experience in production AI/ML systems, strong software engineering practices, and leadership skills.

Core AIOn-siteFull-timePrincipalPythonSQL

Staff Software Engineer - Machine Learning

Apply

Core AIOn-siteFull-timePrincipalPython

Salary

Not specified

Work Location

Richmond, Victoria, Australia, AU

Work Model

On-site

Employment Type

Full-time

Experience Level

Staff

Core Qualifications

Technical (Must-have)

PythonSQLAWSMachine LearningMLOpsLLMTransformersEmbeddingsAirflowKafkaBigQueryCI/CDTest AutomationEvolutionary ArchitectureGenerative AI

Soft Skills

LeadershipMentoringCommunicationStakeholder ManagementCollaborationCuriosityAdaptabilityGrowth MindsetOwnershipProblem Solving

Key Responsibilities

•Lead strategically important AI/ML initiatives, shaping architecture and engineering practices to deliver high-quality product capabilities.
•Support the Engineering Manager in setting technical direction, uplifting ML engineering capability and championing best practices, ethics and engineering excellence.
•Collaborate across functions and specialisations to understand needs, set direction and design solutions aligned to commercial priorities.
•Inform product discovery, delivery planning and technical design with balanced views on feasibility, effort, quality, risk and maintainability.
•Design, build, deploy and operate end-to-end ML products, pipelines and services using Python, modern ML frameworks and AWS.
•Own the production ML lifecycle, including experimentation, versioning, evaluation, deployment, monitoring and continuous improvement.
•Establish robust evaluation frameworks to track performance, detect drift and maintain quality at scale.
•Develop and optimise solutions across product use cases including LLM engineering, relevance, retrieval, ranking and generative AI.
•Leverage or fine-tune third-party models, embeddings, transformers and LLMs in production.
•Build and evolve data and feature foundations for real-time and batch inference, with working fluency in SQL, Airflow, Kafka and BigQuery.
•Contribute to shared ML platform capabilities that accelerate experimentation, delivery and operational maturity across teams.
•Raise the bar for engineering quality, technical judgement and team effectiveness through mentoring, solution guidance and cross-squad collaboration.
•Act as an AI/ML engineering SME, championing the ethical and compliant use of data and helping build REA’s AI/ML reputation internally and externally.

Machine LearningStaff EngineerAI/MLAWSPythonLLMMLOpsREA GroupFull-timeOn-site

Key Responsibilities

•Lead strategically important AI/ML initiatives, shaping architecture and engineering practices to deliver high-quality product capabilities.

•Support the Engineering Manager in setting technical direction, uplifting ML engineering capability and championing best practices, ethics and engineering excellence.

•Collaborate across functions and specialisations to understand needs, set direction and design solutions aligned to commercial priorities.

•Inform product discovery, delivery planning and technical design with balanced views on feasibility, effort, quality, risk and maintainability.

•Design, build, deploy and operate end-to-end ML products, pipelines and services using Python, modern ML frameworks and AWS.

•Own the production ML lifecycle, including experimentation, versioning, evaluation, deployment, monitoring and continuous improvement.

•Establish robust evaluation frameworks to track performance, detect drift and maintain quality at scale.

•Develop and optimise solutions across product use cases including LLM engineering, relevance, retrieval, ranking and generative AI.

•Leverage or fine-tune third-party models, embeddings, transformers and LLMs in production.

•Build and evolve data and feature foundations for real-time and batch inference, with working fluency in SQL, Airflow, Kafka and BigQuery.

•Contribute to shared ML platform capabilities that accelerate experimentation, delivery and operational maturity across teams.

•Raise the bar for engineering quality, technical judgement and team effectiveness through mentoring, solution guidance and cross-squad collaboration.

•Act as an AI/ML engineering SME, championing the ethical and compliant use of data and helping build REA’s AI/ML reputation internally and externally.