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AU: Sydney (45 Clarence St) · AU: Melbourne: (260 Burwood Rd) · Sydney, New South Wales, Australia
Live, first seen by us 62 days agoLocation type: HybridFrom the employer’s posting
Employment type: Full-timeFrom the employer’s posting
Department: Data, AI & Machine LearningFrom the employer’s posting
You’ll build and operate systems rather than train or tune models, and your architecture decisions will directly shape scale, cost, reliability and how fast our teams ship.
The role You will design, build and own the production systems behind Xero’s AI features: the services, pipelines and infrastructure that power LLM-driven and agentic experiences for millions of small businesses every day. This is a software engineering role. You’ll build and operate systems rather than train or tune models, and your architecture decisions will directly shape scale, cost, reliability and how fast our teams ship. You don’t need a machine learning background. We’re looking for strong production engineers, ideally with experience building LLM or agentic systems, and ML depth can be learned on the team.
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Day 62
Similar jobs usually come down between day 6 and day 69.
From 4,301 similar postings that came down. Coming down is not always a hire.
12 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- Experience building and operating production systems for LLM or agentic workloads (orchestration, tool use, evaluation, guardrails, latency and cost management) - Strong system design fundamentals and excellent coding in Python, or another language suited to web-scale services (Go, Java, Kotlin, TypeScript) - Experience with APIs and service design, cloud infrastructure (ideally AWS), CI/CD and observability, with a focus on latency, cost, reliability and SLOs
- Experience running services in production, including on-call and incident response - Solid SQL and experience with large-scale data processing - Excellent communication, with the ability to explain complex technical concepts to business and technical audiences
- Strong system design fundamentals and excellent coding in Python, or another language suited to web-scale services (Go, Java, Kotlin, TypeScript) - Experience with APIs and service design, cloud infrastructure (ideally AWS), CI/CD and observability, with a focus on latency, cost, reliability and SLOs - Experience running services in production, including on-call and incident response
- Experience operationalizing ML or LLM workloads (inference serving, evaluation pipelines) - Familiarity with MLflow, PyTorch or TensorFlow, and data orchestration tools - Distributed processing experience (Spark, Dask)
- Familiarity with MLflow, PyTorch or TensorFlow, and data orchestration tools - Distributed processing experience (Spark, Dask) Apply even if your experience isn't a perfect match! At Xero, we hire based on your skills, passion, and the unique perspective you can bring to enhance our culture and team.
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We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
The role
You will design, build and own the production systems behind Xero’s AI features: the services, pipelines and infrastructure that power LLM-driven and agentic experiences for millions of small businesses every day. This is a software engineering role. You’ll build and operate systems rather than train or tune models, and your architecture decisions will directly shape scale, cost, reliability and how fast our teams ship.
You don’t need a machine learning background. We’re looking for strong production engineers, ideally with experience building LLM or agentic systems, and ML depth can be learned on the team.
Beyond architecture, you’ll lift engineering capability across AI Products by setting standards, mentoring engineers and partnering across Xero to make data usable and systems dependable.
The team
You’ll join AI Products, a diverse, globally distributed team of scientists, engineers, product managers and analysts within our broader Data & AI business.
Engineers here partner closely with Applied Scientists early on to build the interfaces and harnesses that take models into production. They then own the engineering and infrastructure of every ML and AI system shipped into production, from reliability and cost to scale. Together, this collaborative team reduces toil and delivers reliable, intelligent experiences for small businesses.
The team is currently working on
Production ML and AI engineering: Building and operating the platforms, services and practices that support traditional ML models, generative AI and agentic systems in production.
JAX (Just Ask Xero): Powering Xero's conversational GenAI assistant and evolving the underlying capabilities to support increasingly sophisticated, context-aware and agentic experiences.
Intelligent financial workflows: Developing capabilities such as Automated Bank Reconciliation and smart document capture, using ML and AI to match transactions, extract information from bills and receipts, and automate complex tasks.
XeroForce: Building the platform for AI-powered workflows, enabling agents to plan and execute complex tasks across Xero’s products and supporting reliable, reusable agentic experiences at scale.
End-to-end AI product experiences: Integrating AI into customer-facing experiences and product workflows, alongside the backend services, orchestration and infrastructure that make them work.
Where and how you can work
Xero offers a flexible hybrid working model designed to blend the collaboration of office life with the autonomy of remote work. You will have access to our modern office spaces, with expectations around office days and collaborative 'boost days' aligned to help your team connect and ship great code effectively.
Here are some of the things we are looking for
A track record of designing, shipping and operating production-grade backend systems at scale
Experience building and operating production systems for LLM or agentic workloads (orchestration, tool use, evaluation, guardrails, latency and cost management)
Strong system design fundamentals and excellent coding in Python, or another language suited to web-scale services (Go, Java, Kotlin, TypeScript)
Experience with APIs and service design, cloud infrastructure (ideally AWS), CI/CD and observability, with a focus on latency, cost, reliability and SLOs
Experience running services in production, including on-call and incident response
Solid SQL and experience with large-scale data processing
Excellent communication, with the ability to explain complex technical concepts to business and technical audiences
A coaching mindset and the ability to set engineering standards and mentor other engineers
Nice to have
Experience operationalizing ML or LLM workloads (inference serving, evaluation pipelines)
Familiarity with MLflow, PyTorch or TensorFlow, and data orchestration tools
Distributed processing experience (Spark, Dask)
Apply even if your experience isn't a perfect match! At Xero, we hire based on your skills, passion, and the unique perspective you can bring to enhance our culture and team.
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Sydney, New South Wales, Australia
Where and how you can work Xero offers a flexible hybrid working model designed to blend the collaboration of office life with the autonomy of remote work. You will have access to our modern office spaces, with expectations around office days and collaborative 'boost days' aligned to help your team connect and ship great code effectively. Here are some of the things we are looking for
No clear work-authorization passage found. Eligibility is unconfirmed.