Senior ML Engineer (AI Products)
At a glance
Senior Machine Learning Engineering role at Xero. Sydney · full-time.
Pay not stated ML Engineer salary
aimlroles summary, based on the employer's posting.
What you'll do
- Set the architecture and technical direction for distributed systems behind AI features used at scale
- Build and operate reliable services that move models from research into production with Applied Scientists
- Keep the AI Products systems flexible and cost-aware while reducing accumulated technical debt
- Raise engineering standards across the team, mentor junior engineers and improve data usability
What you bring
- At least five years building and running production services at scale in Python or an equivalent language
- Strong system design and coding skills, plus experience owning live services or pipelines and handling incidents and on-call work
- A solid grasp of distributed processing, such as Spark or Dask, and strong SQL ability
- Experience putting ML models or LLM features into production alongside Applied Scientists
Who this fits
This senior engineering role suits someone whose strengths are production software and distributed systems, and who can turn research models into dependable product features. The position is based in Sydney and follows a hybrid working model, with office and collaborative boost days.
From the employer
The role
You will lead the design and implementation of large-scale, production-grade distributed systems that power AI features for millions of daily users. You'll own the architecture decisions that keep our systems flexible, cost-effective, and robust, direct strategy for distributed systems, and manage technical debt across the AI Products estate.
Beyond architecture, your impact lies in lifting the technical capability of the entire AI Products team. You will champion engineering excellence, mentor junior engineers, and collaborate across Xero to enhance data usability - applying modern AI research, including Large Language Models, only once it can be engineered into reliable, production-grade systems.
The team
You will join the AI Products group, a diverse team of scientists, engineers, product managers, and analysts within our broader Data & Science division. As a Machine Learning Engineer, you'll partner closely with Applied Scientists to build the interfaces and harnesses that safely and reliably transition models from research into production. Together, this collaborative team reduces toil and delivers beautiful, data-driven insights 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
5+ years building and operating production Python (or equivalent language) services at scale - this is a software engineering role first; strong system design and coding proficiency are non-negotiable
A track record of owning services or pipelines in production, including operational/on-call responsibility, incident response, and managing technical debt over time
Deep understanding of distributed processing principles (Spark, Dask, or similar) alongside strong SQL capabilities
Demonstrated experience integrating ML models or LLM-based features into production systems - you don't need a research background, but you should be comfortable working alongside Applied Scientists to productionize their work
Familiarity with ML tooling such as MLFlow, TensorFlow, or PyTorch, and data orchestration tools like Airflow or Prefect, is valued but production engineering depth matters more than research exposure
Nice to have: prior experience applying or fine-tuning LLMs in a product context, though this is not a substitute for the core software engineering bar above
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.