The Role

The role & impact

At Xero, ML Engineers are the builders behind the intelligence. As an ML Engineer within the AI Products group, you will design and develop the infrastructure and services that power AI products reaching millions of customers every day. Working closely with Applied Scientists, you will help take models from research environments into reliable, scalable production systems — bridging the gap between experimentation and real-world impact.

This is a role where the work you do genuinely matters. The systems you build sit at the heart of Xero's AI capabilities, helping small businesses save time, make better decisions, and focus on what they do best.

The team & how they connect

The AI Products group sits within Xero's Data & Science function and brings together ML Engineers and Applied Scientists focused on turning data into products that genuinely improve the day-to-day lives of small business owners. The team is globally distributed and works closely across disciplines — engineering, science, product, and analysis — so that AI capabilities move from research into the hands of customers effectively and responsibly. Collaboration and knowledge sharing are core to how this team operates.

The team is currently working on

• A Python-based ML infrastructure built to support both research flexibility and production reliability, including tooling across MLFlow, TensorFlow, and PyTorch
• Data orchestration pipelines using Airflow and Prefect, with distributed processing workloads running on AWS EMR
• Scalable AI services that serve real-time product experiences for millions of Xero users
• The next generation of LLM-powered features, exploring how large language models can reduce toil and surface better insights for small businesses

Where and how you can work

Here are some of the things we are looking for

• Strong coding skills in Python and a solid grasp of system design principles for data and AI applications at scale
• SQL proficiency and familiarity with distributed processing frameworks such as Spark or Dask
• Hands-on experience with ML tooling — frameworks like MLFlow, TensorFlow, or PyTorch, and orchestration tools such as Airflow or Prefect
• The ability to communicate technical concepts clearly to both technical and non-technical audiences
• An interest in how LLM technologies can be applied to real product challenges, and a willingness to learn and experiment in this space
• Comfort working collaboratively across engineering and science disciplines, contributing to shared standards and practices

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.