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Machine Learning Engineer - Training & Dataset Platform (AU remote)

Canva

Machine Learning Engineer - Training & Dataset Platform (AU remote)

Canva

Sydney

·

On-site

·

Full-time

·

4d ago

About the Group/Team

In the AI Platform group — AI Capabilities / Dataset & Training Platform — we build the underlying systems that enable teams across Canva to develop and improve AI features at scale. We focus on making high-quality training data easier to create, manage, and evaluate, while keeping trust, safety, and reliability front-and-centre. We partner closely with ML engineers, applied scientists, product teams, and platform teams to unblock development and lift the baseline for how AI is built at Canva. Our work creates leverage: when we ship, many teams ship faster and safer.

About the Role/Specialty

As a Machine Learning Engineer, you’ll work at the intersection of ML, data systems, and platform engineering to help build and improve the datasets and tooling that enable training and evaluation. We’re looking for someone who enjoys rolling up their sleeves to solve real problems — improving data quality, pipeline reliability, and developer workflows. You’ll contribute to systems that make it easier for teams to run experiments, iterate on models, and measure improvements over time. Your work will directly impact the speed and quality of AI development across Canva.

What you’ll do (responsibilities)

  • You’ll build and improve data pipelines, dataset tooling, and platform components that support ML training and evaluation.

  • You’ll partner with ML and applied science teams to translate training/evaluation needs into scalable platform solutions.

  • You’ll implement quality controls (validation, monitoring, testing) to improve trust in data and pipeline outcomes.

  • You’ll debug issues across data + ML workflows, driving root-cause fixes and preventing repeat incidents.

  • You’ll contribute to engineering standards: code quality, documentation, and operational readiness.

  • You’ll support iteration velocity by improving developer experience for dataset discovery, usage, and experimentation.

What we're looking for

We’re looking for a pragmatic engineer who enjoys solving messy, real-world ML/data problems and shipping improvements that stick. You have solid foundations in ML engineering and data systems, and you care about making workflows reliable, measurable, and easy for others to use. You communicate clearly, collaborate well across disciplines, and take ownership of delivering outcomes (not just tasks). Most importantly, you’re excited to build platform capabilities that help Canva’s AI teams move faster — while keeping quality and trust high.

  • You’re comfortable & have demonstrated experience working with large datasets and understand data preprocessing, feature engineering, and evaluation techniques
  • You have strong programming skills (e.g., Python) and experience with ML frameworks (e.g., Tensor Flow, Py Torch)
  • You enjoy solving complex problems and thinking critically about model performance and trade-offs
  • You’re a collaborative team player who communicates clearly with both technical and non-technical stakeholders
  • You’re excited about working in a fast-paced, product-driven environment and contributing to impactful AI solutions

Don't tick all the boxes? Don't worry about that - nobody does!

We’d still love to hear from you! At Canva, we know that great engineers come from a variety of backgrounds, and we value passion, curiosity, and a willingness to learn just as much as specific experience. If you're excited about this role but don’t tick every box, we encourage you to apply, you might a great fit in ways you didn’t expect!

What's in it for you?

Achieving our crazy big goals motivates us to work hard - and we do - but you'll experience lots of moments of magic, connectivity and fun woven throughout life at Canva, too. We also offer a stack of benefits to set you up for every success in and outside of work.

Here's a taste of what's on offer:

  • Equity packages - we want our success to be yours too
  • Inclusive parental leave policy that supports all parents & carers
  • An annual Vibe & Thrive allowance to support your wellbeing, social connection, office setup & more
  • Flexible leave options that empower you to be a force for good, take time to recharge and supports you personally

Check out lifeatcanva.com for more info.

Other stuff to know

We make hiring decisions based on your experience, skills and passion, as well as how you can enhance Canva and our culture. When you apply, please tell us the pronouns you use and any reasonable adjustments you may need during the interview process.

All interviews are conducted virtually

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.

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关于Canva

Canva

Canva

Series D

An online design and visual communication platform that provides design tools for non-designers.

1,001-5,000

员工数

Sydney

总部位置

$40B

企业估值

评价

4.2

10条评价

工作生活平衡

3.8

薪酬

2.5

企业文化

4.5

职业发展

4.2

管理层

4.3

78%

推荐给朋友

优点

Flexible schedules and hours

Supportive team and leadership

Growth and learning opportunities

缺点

Fast-paced and demanding environment

Heavy workload and long hours

High expectations and pressure

薪资范围

31个数据点

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Mid/L4

Senior/L5

Staff/L6

Junior/L3 · Data Scientist B1

0份报告

$111,685

年薪总额

基本工资

-

股票

-

奖金

-

$94,933

$128,437

面试经验

2次面试

难度

3.0

/ 5

时长

14-28周

体验

正面 0%

中性 50%

负面 50%

面试流程

1

Application Review

2

Online Assessment/Portfolio Review

3

Recruiter Screen

4

Hiring Manager Interview

5

Team Interview

6

Offer

常见问题

Technical Knowledge

Portfolio/Design Questions

Behavioral/STAR

Culture Fit

Past Experience

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