2 months ago
Sydney, Australia or Melbourne, AustraliaSenior
Responsibilities
- Lead the design and implementation of flexible, cost-effective, and robust AI research and production infrastructure at scale
- Manage technical debt and direct distributed systems strategies
- Refactor complex systems and design highly scalable distributed production infrastructure
- Build interfaces and harnesses that transition machine learning models from research to production
- Use Python, SQL, and distributed processing engines to handle web-scale data workloads
- Develop production environments with AI frameworks and data orchestration tools
- Manage cloud workloads via AWS EMR
- Mentor junior engineers and machine learning colleagues
- Champion engineering excellence and improve data usability across Xero
Requirements
- Strong 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 is highly valued
- Knowledge of data orchestration tools is highly valued
- Eagerness to learn and implement Large Language Model technologies in product features
- Ability to communicate complex technical concepts to business and technical audiences
- Coaching mindset and ability to establish engineering standards and mentor junior machine learning colleagues
Benefits
- Flexible hybrid working model combining office and remote work
- Access to modern office spaces and collaborative team boost days
Tech Stack
Categories
About Xero
Xero builds cloud-based accounting software for small businesses and their advisors, covering invoicing, bank reconciliation, payroll, expenses, and reporting. It sells subscriptions and supports an extensive ecosystem of connected bank feeds and third‑party apps via APIs and an app marketplace. Founded in 2006 and headquartered in Wellington, New Zealand, Xero is a public company dual‑listed on the NZX and ASX.