Senior ML/AI Systems Engineer (AI Products)

Xero; Sydney; Hybrid; AUD 180,000 - 240,000; Full time

Job summary

Xero is seeking a leader to design and implement AI research and production infrastructure at scale in Sydney. You will guide architecture, optimize cost and reliability, manage technical debt, and shape strategies for distributed systems that power millions of daily users.

You'll elevate the AI Products team, mentor engineers, and partner across the Data & Science division to improve data usability. The role involves collaborating with ML engineers and scientists to transition research into

Qualifications

• Design and implement scalable AI research and production infrastructure.
• Lead distributed systems strategies and manage technical debt.
• Mentor junior engineers and uplift AI product teams.
• Collaborate across Data & Science to improve data usability and production readiness.

Responsibilities

• Lead the architecture of AI infrastructure at scale.
• Mentor and coach junior engineers in best practices.
• Collaborate with ML engineers and scientists to transition research to production.
• Drive engineering standards and cross-team communication.

Skills

System design

Python

SQL

Communication

Mentoring

Tools

Spark

Dask

Airflow

Prefect

AWS EMR

MLFlow

TensorFlow

PyTorch

Job description

You will lead the design and implementation of AI research and production infrastructure at scale, ensuring our systems remain flexible, cost-effective, and robust. By managing technical debt and directing strategies for distributed systems, your technical decisions will directly influence products that serve millions of daily users.

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, ensuring we solve complex technical challenges with the right methods.

The team / how they connect

You will join the AI Products group, a diverse, globally distributed team of scientists, engineers, product managers, and analysts within our broader Data & Science division. Machine Learning Engineers partner closely with Applied Scientists during the research phase to build interfaces and harnesses that safely transition models from research to production. Together, this collaborative team reduces toil and delivers beautiful, data-driven insights for small businesses.

The team is currently working on

Refactoring complex systems and designing highly scalable, distributed production infrastructure to support next-generation AI features

Harnessing Python, SQL, and distributed processing engines such as Spark or Dask to handle web-scale data workloads

Developing production environments utilizing established AI frameworks, data orchestration tools like Airflow or Prefect, and managing cloud workloads via AWS EMR

Exploring and applying modern Large Language Model technologies to drive continuous product innovation

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

You will bring excellent system design and coding proficiency in Python or alternative languages suited for web-scale AI applications

A deep understanding of distributed processing principles alongside strong SQL capabilities is essential for success

Your exceptional communication skills enable you to easily translate complex technical concepts for both business and technical audiences

Having a natural coaching mindset will allow you to successfully establish engineering standards and mentor junior machine learning colleagues

An eagerness to learn, master, and implement Large Language Model technologies into product features

Experience utilizing frameworks like MLFlow, TensorFlow, or PyTorch, combined with knowledge of data orchestration tools, will be highly valued