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Sydney
7 Jul 2026
Senior Engineer - ML Systems (AI Products) logo

Senior Engineer - ML Systems (AI Products)

Xero

Sydney
7 Jul 2026
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Senior Engineer - ML Systems (AI Products)

Xero seeks a Senior Engineer to lead design and implementation of large-scale distributed systems powering AI features. The role involves owning architecture decisions, mentoring engineers, and collaborating with Applied Scientists to productionize ML models. Requires 5+ years in production Python services, distributed processing, and ML integration.

Core AIHybridFull-timeSeniorPythonSQL

Senior Engineer - ML Systems (AI Products)

Xero seeks a Senior Engineer to lead design and implementation of large-scale distributed systems powering AI features. The role involves owning architecture decisions, mentoring engineers, and collaborating with Applied Scientists to productionize ML models. Requires 5+ years in production Python services, distributed processing, and ML integration.

Apply
Core AIHybridFull-timeSeniorPython

Salary

Not specified

Work Location

Sydney, New South Wales, Australia, AU

Work Model

Hybrid working model blending office collaboration with remote autonomy

Experience Required

5 years

Employment Type

Full-time

Experience Level

Senior (5+ years)

Core Qualifications

Technical (Must-have)
PythonSQLApache SparkDaskAWSKubernetesMachine LearningLLMMLflowTensorFlowPyTorchApache AirflowPrefectSystem DesignDistributed Systems
Soft Skills
MentoringEngineering ExcellenceCollaborationTechnical Leadership

Preferred Qualifications

Technical (Nice-to-have)
Fine-tuning LLMs

Key Responsibilities

  • •Lead design and implementation of large-scale, production-grade distributed systems for AI features
  • •Own architecture decisions for flexibility, cost-effectiveness, and robustness
  • •Direct strategy for distributed systems and manage technical debt
  • •Champion engineering excellence and mentor junior engineers
  • •Collaborate with Applied Scientists to productionize ML models and LLMs
  • •Design and build scalable production infrastructure for generative AI
  • •Deploy to production environments on AWS and Kubernetes
Senior EngineerMachine LearningDistributed SystemsPythonAWSKubernetesLLMData EngineeringAI ProductsHybrid
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