Senior Research Engineer - Design Generation
Company Description
Join the team redefining how the world experiences design
Hiya, 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
The buzzing Canva London campus features several buildings around beautiful leafy Hoxton Square in Shoreditch. While our global headquarters is in Sydney, Australia, London is our HQ for Europe, with all kinds of teams based here, plus event spaces to gather our team and communities.
You'll experience a warm welcome from our Vibe team at front of house, amazing home cooked food from our Head Chef and a variety of workspaces to hang out with your team mates or get solo work done. That said, we trust our Canvanauts to choose the balance that empowers them and their team to achieve their goals and so you have choice in where and how you work.
Job Description
At Canva, our mission is to empower the world to design. We’re building AI that feels magical and lands real impact for millions of people - helping anyone create with confidence. We’re looking for a Machine Learning Engineer with strong Research Engineer / Applied Scientist instincts to bridge cutting-edge research and production systems, owning the pipelines, tooling, and experimentation loops that turn ambitious ideas into scalable, shippable reality.
About the team:
The Design Generation team builds machine learning systems that generate and enhance graphic designs directly in the Canva editor. We combine research and engineering to make complex design tasks simple and accessible for everyone. The team includes Research Scientists and Machine Learning Engineers working closely with backend, frontend, and platform teams. This role sits at the intersection of research and engineering: sometimes leaning into applied research and hypothesis testing, other times taking deep ownership of reusable training, inference, and evaluation pipelines that multiple teams depend on.
You’ll play a key role in:
Standardising and scaling evaluation, training, and data pipelines
Helping research ideas move quickly from prototype to production
Ensuring our solutions fit coherently into Canva’s broader AI and product stack
By building durable foundations and enabling fast iteration, you’ll directly support Canva’s vision to empower the world to design.
About the role:
As a Machine Learning Engineer, you’ll partner closely with Research Scientists to test hypotheses quickly, while also owning the engineering work required to make those ideas reliable, reusable, and production-ready.
You’ll take responsibility for shared pipelines and infrastructure that power multimodal generative systems—helping unblock research velocity, reduce duplicated effort, and improve system performance at scale. Your work will directly influence the quality, speed, and reliability of AI-powered design features used by millions of Canva users.
What you'll do in the role:
Partner closely with Research Scientists on multimodal generative AI, translating research ideas and hypotheses into practical, testable systems
Own and evolve reusable training, inference, and evaluation pipelines, working across teams to standardise where possible
Convert experimental Python research code into scalable, maintainable, and testable production code
Design, build, and maintain large-scale data and evaluation pipelines that support rapid experimentation and reliable comparisons
Support fast hypothesis testing by enabling lightweight experiments and clear evaluation signals
Optimise models and pipelines for real-world constraints, including performance, latency, cost, and reliability
Collaborate with stakeholders across Canva (including other AI teams) to align on shared approaches and avoid duplicated effort
Stay ahead of industry trends and translate cutting-edge AI research into actionable product features
Contribute to team roadmaps by identifying data, evaluation, or infrastructure bottlenecks and proposing solutions
You're likely a match if you have:
Strong software engineering skills in Python, with experience building production-grade ML systems
Experience owning training, inference, and evaluation pipelines for machine learning models
Experience with RGBA data and layered image representations
Hands-on experience with large-scale ML data workflows (e.g. Ray or similar frameworks), including data loading, batching, sharding, and versioning
Solid understanding of ML training requirements—you know what a “good system” looks like and can anticipate downstream issues
Experience working with cloud infrastructure (AWS) and distributed storage systems
Ability to operate comfortably in ambiguous problem spaces, balancing research exploration with engineering rigour
Strong communication skills and a collaborative mindset—you can work effectively with researchers, MLEs, and software engineers across disciplines
A collaborative approach, comfortable taking ownership and iterating quickly.
Nice to have:
Experience working with multimodal data (e.g., image–text pairs, design assets).
Experience building synthetic data generation pipelines.
Experience building impactful end-to-end demos that showcase research impact.
Familiarity with evaluation frameworks, data quality metrics, and model monitoring systems.
Prior research experience, including authorship or co-authorship of research papers, or contributions to open-source datasets, benchmarks, or ML tooling.
Additional Information
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 range 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.
We celebrate all types of skills and backgrounds at Canva so even if you don’t feel like your skills quite match what’s listed above - we still want to hear from you!
Please note that interviews are conducted virtually.
About the job
Apply for this position
Senior Research Engineer - Design Generation
Company Description
Join the team redefining how the world experiences design
Hiya, 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
The buzzing Canva London campus features several buildings around beautiful leafy Hoxton Square in Shoreditch. While our global headquarters is in Sydney, Australia, London is our HQ for Europe, with all kinds of teams based here, plus event spaces to gather our team and communities.
You'll experience a warm welcome from our Vibe team at front of house, amazing home cooked food from our Head Chef and a variety of workspaces to hang out with your team mates or get solo work done. That said, we trust our Canvanauts to choose the balance that empowers them and their team to achieve their goals and so you have choice in where and how you work.
Job Description
At Canva, our mission is to empower the world to design. We’re building AI that feels magical and lands real impact for millions of people - helping anyone create with confidence. We’re looking for a Machine Learning Engineer with strong Research Engineer / Applied Scientist instincts to bridge cutting-edge research and production systems, owning the pipelines, tooling, and experimentation loops that turn ambitious ideas into scalable, shippable reality.
About the team:
The Design Generation team builds machine learning systems that generate and enhance graphic designs directly in the Canva editor. We combine research and engineering to make complex design tasks simple and accessible for everyone. The team includes Research Scientists and Machine Learning Engineers working closely with backend, frontend, and platform teams. This role sits at the intersection of research and engineering: sometimes leaning into applied research and hypothesis testing, other times taking deep ownership of reusable training, inference, and evaluation pipelines that multiple teams depend on.
You’ll play a key role in:
Standardising and scaling evaluation, training, and data pipelines
Helping research ideas move quickly from prototype to production
Ensuring our solutions fit coherently into Canva’s broader AI and product stack
By building durable foundations and enabling fast iteration, you’ll directly support Canva’s vision to empower the world to design.
About the role:
As a Machine Learning Engineer, you’ll partner closely with Research Scientists to test hypotheses quickly, while also owning the engineering work required to make those ideas reliable, reusable, and production-ready.
You’ll take responsibility for shared pipelines and infrastructure that power multimodal generative systems—helping unblock research velocity, reduce duplicated effort, and improve system performance at scale. Your work will directly influence the quality, speed, and reliability of AI-powered design features used by millions of Canva users.
What you'll do in the role:
Partner closely with Research Scientists on multimodal generative AI, translating research ideas and hypotheses into practical, testable systems
Own and evolve reusable training, inference, and evaluation pipelines, working across teams to standardise where possible
Convert experimental Python research code into scalable, maintainable, and testable production code
Design, build, and maintain large-scale data and evaluation pipelines that support rapid experimentation and reliable comparisons
Support fast hypothesis testing by enabling lightweight experiments and clear evaluation signals
Optimise models and pipelines for real-world constraints, including performance, latency, cost, and reliability
Collaborate with stakeholders across Canva (including other AI teams) to align on shared approaches and avoid duplicated effort
Stay ahead of industry trends and translate cutting-edge AI research into actionable product features
Contribute to team roadmaps by identifying data, evaluation, or infrastructure bottlenecks and proposing solutions
You're likely a match if you have:
Strong software engineering skills in Python, with experience building production-grade ML systems
Experience owning training, inference, and evaluation pipelines for machine learning models
Experience with RGBA data and layered image representations
Hands-on experience with large-scale ML data workflows (e.g. Ray or similar frameworks), including data loading, batching, sharding, and versioning
Solid understanding of ML training requirements—you know what a “good system” looks like and can anticipate downstream issues
Experience working with cloud infrastructure (AWS) and distributed storage systems
Ability to operate comfortably in ambiguous problem spaces, balancing research exploration with engineering rigour
Strong communication skills and a collaborative mindset—you can work effectively with researchers, MLEs, and software engineers across disciplines
A collaborative approach, comfortable taking ownership and iterating quickly.
Nice to have:
Experience working with multimodal data (e.g., image–text pairs, design assets).
Experience building synthetic data generation pipelines.
Experience building impactful end-to-end demos that showcase research impact.
Familiarity with evaluation frameworks, data quality metrics, and model monitoring systems.
Prior research experience, including authorship or co-authorship of research papers, or contributions to open-source datasets, benchmarks, or ML tooling.
Additional Information
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 range 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.
We celebrate all types of skills and backgrounds at Canva so even if you don’t feel like your skills quite match what’s listed above - we still want to hear from you!
Please note that interviews are conducted virtually.