6 days ago
Sydney, Australia or Melbourne, AustraliaSenior
Responsibilities
- Lead the design and implementation of flexible, cost-effective, robust AI research and production infrastructure at scale.
- Direct distributed-systems strategy, manage technical debt, and design scalable production infrastructure for next-generation AI features.
- Build web-scale data workloads using Python, SQL, and distributed processing engines such as Spark or Dask.
- Develop production environments with AI frameworks and data orchestration tools such as Airflow or Prefect, while managing cloud workloads through AWS EMR.
- Partner with Applied Scientists to transition models from research into production and improve data usability across Xero.
- Mentor junior engineers and strengthen the technical capability and engineering standards of the AI Products team.
Requirements
- Excellent system design and coding proficiency in Python or alternative languages suited to web-scale AI applications.
- Deep understanding of distributed processing principles and strong SQL capabilities.
- Experience with MLFlow, TensorFlow, or PyTorch and knowledge of data orchestration tools are highly valued.
- Ability to communicate complex technical concepts to business and technical audiences.
- Interest in learning and implementing Large Language Model technologies in product features.
- Ability and willingness to establish engineering standards and mentor junior machine-learning colleagues.
Benefits
- Flexible hybrid working model combining office and remote work, with office days and collaborative boost days.