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Machine Learning Engineer - Data - AI Research

Machine Learning Engineer - Data - AI Research

black.aiWorkFromHome, Auckland, New Zealand
7 hours ago
Job description

Company Description

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.

Job Description

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. 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
  • You’re probably a match if you have :

  • A strong 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).
  • Additional Information

    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.

  • 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.

    #J-18808-Ljbffr

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    Data Engineer • WorkFromHome, Auckland, New Zealand

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