Staff Software Engineer - Machine Learning
REA Group
Staff Software Engineer - Machine Learning
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. This permanent, on-site role in Melbourne or Sydney involves leading strategic AI/ML initiatives, designing end-to-end ML products, and mentoring engineers. The ideal candidate has deep experience in production AI/ML systems, strong software engineering practices, and expertise in Python, SQL, and modern ML frameworks.
Staff Software Engineer - Machine Learning
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. This permanent, on-site role in Melbourne or Sydney involves leading strategic AI/ML initiatives, designing end-to-end ML products, and mentoring engineers. The ideal candidate has deep experience in production AI/ML systems, strong software engineering practices, and expertise in Python, SQL, and modern ML frameworks.
Salary
Core Qualifications
Technical (Must-have)
Soft Skills
Key Responsibilities
- Lead strategically important AI/ML initiatives, shaping architecture and engineering practices.
- Support the Engineering Manager in setting technical direction and uplifting ML engineering capability.
- Collaborate across functions 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.
- Contribute to shared ML platform capabilities that accelerate experimentation, delivery, and operational maturity.
- Raise the bar for engineering quality, technical judgement, and team effectiveness through mentoring and cross-squad collaboration.
- Act as an AI/ML engineering SME, championing ethical and compliant use of data.