Senior Machine Learning Engineer

Xero

Senior Machine Learning Engineer building production-grade distributed systems for Xero’s AI features. Deploying ML and LLM capabilities through Python, SQL, AWS, Kubernetes, and Spark.

Posted 9/2/2026full-timeToronto • 🇨🇦 CanadaSenior💰 CA$185,000 - CA$225,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing large-scale distributed systems, with a strong focus on Python, SQL, and Spark for AI applications. Proven ability to manage technical debt, mentor engineers, and collaborate effectively with cross-functional teams to enhance data usability.

Highest-signal resume keywords

Python Service DevelopmentDistributed Systems ArchitectureTechnical Debt ManagementLarge Language Model IntegrationData Orchestration Tools

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLSparkDaskSystem DesignIncident ResponseML Model IntegrationLLM ApplicationData Workloads ManagementProduction Infrastructure Design

Soft Skills

MentoringCollaborationEngineering Excellence Advocacy

Tools & Technologies

AWSKubernetesMLFlowTensorFlowPyTorchAirflowPrefect

Industry Keywords

Distributed Processing PrinciplesAI FeaturesData UsabilityProduction Systems

Tech Stack

Tools & technologies

AirflowAWSDistributed SystemsKubernetesPythonPyTorchSparkSQLTensorflow

About the role

Key responsibilities & impact

Lead the design and implementation of large-scale, production-grade distributed systems powering AI features for millions of daily users
Own architecture decisions to keep systems flexible, cost-effective, and robust
Direct distributed-systems strategy
Manage technical debt across the AI Products estate
Champion engineering excellence across the AI Products team
Mentor junior engineers
Collaborate across Xero to enhance data usability
Partner with Applied Scientists to build interfaces and harnesses that transition models from research into production
Design and build scalable distributed production infrastructure for generative AI features
Use Python, SQL, Spark, or Dask to handle web-scale data workloads
Deploy systems to AWS and Kubernetes
Integrate production-ready Large Language Model technologies into product features
Reduce toil and deliver data-driven insights for small businesses

Requirements

What you’ll need

5+ years building and operating production Python (or equivalent language) services at scale
Strong system design and coding proficiency
Track record of owning services or pipelines in production
Operational/on-call responsibility and incident response experience
Experience managing technical debt over time
Deep understanding of distributed processing principles, including Spark, Dask, or similar
Strong SQL capabilities
Experience integrating ML models or LLM-based features into production systems
Comfortable working alongside Applied Scientists to productionize research
Familiarity with MLFlow, TensorFlow, or PyTorch
Familiarity with data orchestration tools such as Airflow or Prefect
Prior LLM application or fine-tuning experience is nice to have, not required

Benefits

Comp & perks

Annual bonus eligibility for permanent employees
Equity (RSU) programs for permanent employees
Performance-based cash or equity (RSUs) incentives depending on role level and company performance
World-class health, wellness, and retirement programs
Wellbeing days
Generous leave
Dedicated professional development budgets
Flexible hybrid working model
Modern office spaces
Collaborative 'boost days'