Staff Machine Learning Engineer - Dataset & Training Platform
Staff Machine Learning Engineer - Dataset & Training Platform
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Not Disclosed
Salary Not Disclosed
1 Vacancy
Job Description
Join the team redefining how the world experiences design.
Hey gday mabuhay kia ora hallo vtejte!
Thanks for stopping by. We know job hunting can be a little time consuming and youre probably keen to find out whats on offer so well 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 we trust our Canvanauts to choose the balance that empowers them and their team to achieve their goals.
What youd be doing in this role
As Canva scales change continues to be part of our DNA. But we like to think thats all part of the fun. So this will give you the flavour of the type of things youll be working on when you start but this will likely evolve.
At the moment this role is focused on:
- Architecting foundational AI Platform capabilities making key technical decisions that impact how models are trained and deployed across Canva.
- Leading cross-team initiatives to consolidate and improve dataset and training capabilities working with stakeholders across multiple engineering and research teams.
- Building and maintain paved roads for high-performance distributed data processing and training systems optimising for cost efficiency and developer experience.
- Driving technical strategy discussions weighing platform stability needs against product velocity requirements.
- Mentoring other engineers and contribute to growing Canvas AI platform engineering capabilities.
- Solving complex technical challenges spanning multiple parts of the ML stack.
Youre probably a match if:
- You have over 5 years of experience building and scaling ML training systems with hands-on experience in distributed training model lifecycle management and large-scale data processing.
- You have a proven track record of designing and implementing foundational AI/ML infrastructure that supports multiple teams and use cases.
- You have experience setting technical direction making architectural decisions and influencing engineering practices across organisations.
- You possess a strong understanding of distributed computing container orchestration (Kubernetes) and cloud infrastructure (preferably AWS).
- You are fluent in Python with deep knowledge of ML frameworks (PyTorch TensorFlow) and modern tools (W&B Ray Anyscale).
- You have a strong understanding of generative AI systems including LLMs multimodal models and foundation model fine-tuning.
- You have the ability to balance long-term platform investments with immediate business needs making pragmatic technical decisions.
- You have experience working with product teams research and other engineering specialties to understand and address diverse technical requirements.
- You have a track record of growing other engineers and contributing to technical culture and standards.
- You have experience with infrastructure-as-code and an understanding of performance optimisation.
- You consider GitOps principles for automation and deployment a plus.
About the team
Canvas GenAI Platform Group is responsible for the delivery of Capabilities and Solutions which support ML and AI initiatives from early ideation and prototyping through to scaling to meet the needs of millions of Canva users in production. We empower thousands of engineers and product managers to deliver amazing product features which harness the power of cutting-edge technologies.
Dataset & Training Platform team specifically focuses on the foundational Capabilities that power model training dataset management and AI/ML workflows. Were building the infrastructure that enables Canvas AI-first future supporting everything from generative design models to intelligent automation systems that serve millions of users worldwide.
Whats in it for you
Achieving our crazy big goals motivates us to work hard and we do but youll 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.
Heres a taste of whats 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 support you personally
Check out 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 dont feel like your skills quite match whats listed above we still want to hear from you!
We see AI as a powerful amplifier of creativity and technology at evolving how we assess AI skills in our Technology hiring experience - youll tackle interactive real-time challenges that reflect the kind of work we do. In some interviews you may also be asked to solve a problem using an AI tool to show how you approach challenges with tech by your side. Your recruitment partner will walk you through what to 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 celebrate all types of skills and backgrounds at Canva so even if you dont feel like your skills quite match whats listed above - we still want to hear from you!
Please note that interviews are conducted virtually.
Remote Work :
Yes
Employment Type :
Full-time
Employment Type
Remote
