Senior Machine Learning Engineer - Content ML (AU remote)

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Work mode

Remote From the posting source checked Jun 20, 2026

In-office days

0 days From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Company

Equity

Offered From the posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Senior Machine Learning Engineer - Content ML (AU remote) Remote | Melbourne, VIC, Australia Company Description: Join the team redefining how the world experiences design. Hey, g'day, mabuhay, kia ora,你好, hallo, vítejte! Thanks for stopping by. We know job hunting can be a little time consuming and you're probably keen to find out what's on offer, so we'll get straight to the point. Where and how you can work Our flagship campus is in Sydney, with a second campus in Melbourne and co-working spaces in Brisbane, Perth & Adelaide. You have flexibility in how and where you work - whether that's from one of our spaces, from home, or a mix of both. This role is remote-friendly within Australia , so you can choose the setup that empowers you and your team to do your best work. Job Description: About the team Join the innovation powerhouse - Content Machine Learning team at Canva! Our vision is to empower all our users with the safest and highest quality content at scale. We build models and human-in-the-loop workflows to amplify our content review efforts so that we can: Unlock review operations with review automation Close the loop for feedback to our models and raise the quality bar Ensure the safety of our library for all our users, including students Finally, our crazy big goal is to build an automated review system with humans at the heart of operations, leading the continuous improvement and evolution of the system. What you'd be doing in

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