Senior Machine Learning Engineer - Design Enablement

Key Skills

Algorithms, Apache Kafka, AWS, Azure, Continuous Integration & Continuous Delivery - CI/CD, Linux Operating system, Machine learning techniques, NumPy, PyTorch, R Programming, Snowflake, UI design, UX design

Job Description

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. We also have a campus in Melbourne and co-working spaces in Brisbane, Perth and Adelaide. But you have choice in where and how you work. That means if you want to do your thing in the office (if you're near one), at home or a bit of both, it's up to you.

What you’d be doing in this role

As Canva scales change continues to be part of our DNA. But we like to think that's all part of the fun. So this will give you the flavour of the type of things you'll be working on when you start, but this will likely evolve.

At the moment, this role is focused on:

• Generating and enriching Design AI datasets, in particular for design generation and design editing models (our most important models in Canva).
• Building and putting into production ML training data pipelines at scale.
• Building model training tooling for Design AI machine learning engineers.

You're probably a match if

Necessary:

• You will have 2-5 years of industry experience building and deploying machine learning models with a product/SaaS company, preferably using Kubernetes on AWS.
• You have a strong understanding of Computer Science/Engineering fundamentals and first principles covering system design, data structures, architecture, and design patterns.
• You demonstrate strong coding proficiency in Python, in particular multiprocessing, and/or Java.
• You are familiar with ML technologies like PyTorch, Argo Workflows, multi-GPU training.

Beneficial:

• Experience with Snowflake.
• Familiarity with the AWS ecosystem.
• Familiarity with CI/CD concepts and the machine learning life cycle.
• Strong SQL skills.

About the team

The engineers working on the Design Enablement team are responsible for the delivery of Machine Learning (ML) at scale in the design AI space. Our mission is to empower Canva to build Design AI magical product experiences which include supporting the needs of all design AI teams from a dataset perspective, doing R&D work ourselves, as well as immediate feature delivery.

2024 is an incredible time to join the team. Design AI is one of the key strategic initiatives for Canva. Our team is small but growing rapidly. We build models that would be core of user experience, and support machine learning engineers across many teams from a platform perspective.

We are looking for engineers with a strong backend engineering background and knowledge of machine learning, who thrive in fast-paced high-energy environments, to help us support Design AI projects through data engineering, generating and enriching large ML training datasets and building tools for our Design AI machine learning engineers.

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.

Please note that interviews are conducted virtually.