Machine Learning Engineer - Data - AI Training

About the Role

As a Research MLE at Canva, you'll be responsible for high-performance data acquisition, processing, and annotation to enable the training of cutting-edge models. Your focus will be on sourcing data, automation, building performant infrastructure for filtering and analyzing, and dealing with petabyte-scale data. You'll be the crucial link that makes novel model development, training, and evaluation possible, accelerating Canva's cutting-edge research.

Key Focus Areas

• Data Acquisition: Developing scalable tools and pipelines for acquiring diverse datasets from multiple sources
• Curation: Engineering robust solutions for filtering, deduplication, quality assessment, and curating data that meets specific research requirements and model training criteria
• Data Infrastructure: Developing high-throughput tools for interfacing with large-scale data pools, enabling efficient querying, sampling, and extracting valuable statistical insights and patterns

Primary Responsibilities

• Work alongside research teams to ensure continuous flow of high-quality data toward active projects, understanding their specific dataset requirements and delivery timelines
• Curate targeted subsets of data using ML techniques including clustering, embedding-based similarity search, and automated quality scoring
• Extract, visualize, and communicate actionable insights about dataset composition, distributions, biases, and statistical properties to inform research decisions
• Build performant, parallel algorithms for gathering and processing data at scale, optimizing for both throughput and cost-efficiency across distributed systems
• Engineer intuitive interfaces and tooling to help researchers explore, sample, and interact with large datasets without requiring deep infrastructure knowledge
• Work with paired multimodal data (text-image, audio-video, etc.), ensuring alignment quality, handling synchronization challenges, and maintaining multimodal correspondence
• Leverage high-performance parallel computing frameworks (Ray, Spark, torch.distributed, DeepSpeed, etc) and cloud infrastructure for distributed data operations on petabyte-scale datasets

Senior Research Engineer - Datasets

• Employees can work remotely
• Full-time
• Recruitment type: Permanent

Company Description

Join the team redefining how the world experiences design.

Hey, hello, 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 office is in Sydney, Australia, but we've made our way from down under, to a hub in San Francisco, which is now home to our US operations. We offer flexibility in how and where you work. We trust our Canvanauts to choose the balance that empowers them and their team to achieve their goals.

Job Description

At Canva, our mission is to empower the world to design. To ensure our generative AI models are truly helpful, we are seeking a talented Research Engineer to build the foundational datasets and systems that fuel our next-generation generative AI models and evaluation capabilities.

About the role:

In this foundational role, you will be the expert on what truly fuels our models: data. You'll own the end-to-end lifecycle of our critical datasets, from curating nuanced human feedback on design quality to pioneering machine learning for high-quality synthetic data generation. This unique position calls for a data-first thinker with a strong design sensibility, passionate about building the high-quality ground truth at scale that will define the future of creativity by ensuring our models align with human taste and intent.

At the moment, this role is focused on:

• Statistical Analysis & Insights: Applying robust statistical methodologies to analyze data, identify significant trends, and derive actionable insights. This includes hypothesis testing, regression analysis, and determining statistical significance to validate model performance and user preferences.

• Human Feedback Data Curation: Owning the design, processing, cleaning, and strategic curation of large-scale, subjective human feedback on design quality, which is the lifeblood of our models.

• Synthetic Data Generation: Using generative AI and machine learning techniques to create novel, high-quality synthetic data that augments our training sets and improves model capabilities.

• Alignment Analysis & Evaluation Design: Designing methods to analyze outputs from both human and automated systems to deeply understand and measure our models' alignment with user preferences.

Primary Responsibilities:

• Design and build scalable pipelines for processing and curating large datasets of human design feedback.

• Research and develop ML models to generate high-quality synthetic data for training and fine-tuning.

• Own the design and implementation of human evaluation workflows, including creating guidelines and quality rubrics.

• Prepare datasets for automated evaluation systems and conduct deep analysis of their outputs to provide robust signals on model performance and human alignment.

• Design and analyze experiments to measure the real-world impact of our models on design quality.

• Conduct deep-dive analyses into model performance to identify failure modes and guide future development.

You’re probably a match if you have:

• A strong aesthetic sense, with a background or demonstrated passion for visual design or human-computer interaction.

• Strong proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow).

• Extensive experience with designing and implementing large-scale data processing workflows using libraries like Pandas and data warehousing solutions such as Snowflake.

• Solid understanding of statistical methods, including experimental design, A/B testing, and quality evaluation systems.

• Experience with generative AI and synthetic data generation is highly desirable.

Nice to have:

• Experience with cloud platforms (e.g., AWS, GCP, Azure) for data storage, processing, and MLOps related to dataset management.

• Experience with MLOps practices and tools specifically for data versioning, lineage, and pipeline automation.

• Ability to develop data visualization or data collection interfaces (e.g., TypeScript, Python).

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.

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, and Auckland, NZ. 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 or New Zealand, so you can choose the setup that empowers you and your team to do your best work.