Top AI & Machine Learning Jobs in Melbourne, VIC

Build and operate AI enablement platforms, internal skills marketplaces, and AI tool distribution systems used by engineering teams. Develop agent skills and remediation agents, establish AI engineering best practices, and manage production reliability through monitoring, runbooks, and rollback planning. Collaborate with AWS, Microsoft, and GitHub on early-access technologies while influencing technical direction and supporting a growing AI-focused team.

Leads Xero’s global data science, analytics, ML, and AI strategy across multiple product areas. The role manages and scales a multidisciplinary organization, advises executive leadership, oversees AI governance, model risk, data quality, privacy, experimentation, and enterprise data architecture, and drives AI-powered products including chatbots and agentic workflows. It also establishes operating models, develops leaders, manages strategic risks, and partners cross-functionally to deliver company-wide data and AI impact.

Design, build, and operate an internal AI skills marketplace and distribution platform. Own end-to-end delivery from experimentation to production, create runbooks, monitoring, rollback plans, and provide guidance on authoring agent skills while collaborating with vendors and engineering teams.

Build and rapidly deploy internal AI-powered tools and automations that reduce operational toil. Integrate Jira, Confluence, Workday, and data warehouses through APIs; automate reporting, headcount management, and roadmapping workflows; evaluate custom, low-code, and SaaS solutions; prototype scalable AI-enabled improvements; and mentor operations teams in modern AI tooling.

Develop and deploy machine learning products and services by translating complex business problems into applied research programs. Build robust data pipelines and reusable code in Python or Scala, develop and evaluate applications involving NLP, computer vision, and LLMs, and monitor algorithms at scale. The role also involves managing research risks, collaborating cross-functionally, mentoring colleagues, communicating complex findings, and raising scientific and engineering standards.

Lead design and implementation of AI research and production infrastructure. Mentor junior engineers, and collaborate to enhance data usability, solving complex technical challenges.

Lead design and implementation of large-scale distributed production systems powering generative AI features. Own architecture, mentor engineers, manage technical debt, operationalize ML/LLM models, and collaborate with scientists to productionize research using Python, SQL, Spark/Dask, AWS, and Kubernetes.

Develop and improve data and AI governance frameworks, translate policies into practical guidance, deliver data and AI literacy programs, and advise cross-functional teams on responsible AI, privacy, risk, transparency, bias, and regulatory compliance. The role partners with Product, Security, Privacy, Regulatory, Risk, and engineering teams to implement governance across Xero.