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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in leading high-performing teams of engineers, focusing on MLOps maturity and the development of production-grade ML infrastructure. Capable of translating business goals into actionable engineering plans while ensuring system health and delivery rigor.
Highest-signal resume keywords
Team LeadershipMLOps MaturityTechnical ArchitectureProduction Code DebuggingMachine Learning Systems
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
System DesignEngineering Trade-offsAI-native WorkflowsProduction ML InfrastructureCash Flow ForecastingTransaction MatchingDocument CapturePrototype to Production TransitionObservabilityDelivery Roadmaps
Soft Skills
CoachingDeveloping EngineersGenuine Curiosity
Tools & Technologies
JAXAI Systems
Industry Keywords
Machine LearningAISoftware Development LifecycleOperational RealitiesInclusive Team
About the role
Key responsibilities & impact- Lead a high-performing, inclusive team of ML and platform engineers
- Turn research and models into production-grade ML infrastructure running at scale
- Balance predictable delivery with system health
- Lead MLOps maturity and observability
- Manage the operational realities of running AI systems in production
- Work with staff and principal engineers on technical architecture
- Focus on team growth and delivery rigour
- Champion AI-native workflows across the software development lifecycle
- Partner with Applied Science, Data Engineering and Product
- Move ideas from prototype to production
- Support production ML infrastructure and MLOps for Xero's AI-native product suite
- Work on systems powering JAX, Xero's conversational GenAI assistant
- Support Auto Bank Rec and smart document capture, including AI-powered transaction matching and extraction from bills and receipts
- Extend cash flow forecasting and other embedded ML capabilities
Requirements
What you’ll need- Strong track record of leading, coaching and developing engineers
- Experience building team capability over time
- Strong technical judgement across architecture, system design and engineering trade-offs
- Experience translating business goals into executable engineering plans
- Experience balancing short-term delivery against long-term system health
- Experience delivering roadmaps predictably in fast-paced, evolving environments
- Comfortable writing, reviewing or debugging production code
- Experience with machine learning or AI systems is a bonus rather than a requirement
- Genuine curiosity about machine learning and AI
- Working rights for the country this role is based in, or ability to obtain visa assistance or sponsorship
Benefits
Comp & perks- Flexible working model with the option to work in a hybrid capacity
- Remote work options combined with office spaces and team boost days
- Fair and supportive recruitment experience
- Recruitment process accommodations or adjustments, including modified interview format, additional assessment time, and assistive technology
- Potential visa assistance or sponsorship
- Background checks and consideration for other current or future opportunities