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Senior Machine Learning Engineer - Bardi, Italia - Canva
Descrizione
Join the team redefining how the world experiences design. Hey, g'day, mabuhay, kia ora, ??, hallo, vítejteThanks 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, we trust our Canvanauts to choose the balance that empowers them and their team to achieve their goals.
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: Content Understanding and Tagging: Develop and refine machine learning models to enhance understanding of our >130M elements and templates.
As well as developing accurate and scalable tagging methodologies for all our content types (including style, semantic, and locale-specific tagging), you'll also work on ML generated metadata to fuel our Magic products, including object detection, saliency prediction, segmentation, description generation, and many more.
Data-Driven Content Strategy:
Analyse and preprocess data to gain insights into the volume and quality of our content library. Drive decisions to improve content strategy, relevance and user experience, particularly in LOTE (Languages Other Than English) markets.
Content Enrichment Ecosystem Development:
Contribute to the creation of a content enrichment ecosystem that integrates (semi-)automated processes for content production. Focus on improving metadata quality, search effectiveness, and enriching AI training datasets. Human-in-the-Loop ML Training: Build and maintain end-to-end human-in-the-loop machine learning processes. Ensure continuous and effective development of ML models, maximising the use of enriched content.
Cross-Team Collaboration:
Work closely with data specialists, software engineers, and product owners across Canva to identify business and growth opportunities. Share knowledge and collaborate to avoid duplication of efforts in content enrichment.
Quality Assessment and Scalability:
Continuously measure and improve label quality to enhance precision and recall our enriched data.
Focus on improving the scalability, speed, and performance of existing models to support high-quality training data for all ML teams at Canva.
Effective Communication:
Clearly articulate statistical analysis, modelling, experiments, and results to both technical and non-technical audiences, ensuring alignment and understanding across teams.
You're probably a match if You have 5 years of industry experiencein the machine learning /software engineering role with a Product/SaaS company, visual AI experience preferred.
You are experienced in building and deploying machine learning models and have a strong understanding of end-to-end machine learning pipelines and components.
You have great research skills with the ability to stay abreast of the latest developments in deep learning and AI.
You are capable to translate cutting-edge research into practical solutions that enhance Canva's content library and user experience.Content-Centric Focus:
you have a keen interest or prior experience in content-related machine learning projects, such as semantic tagging, content classification, and visual content understanding, is highly desirable.
You are proficient in Python coding, interviews will be in Python.You are familiar with several of the following:
PyTorch, Kubernetes, Docker, Solr/ElasticSearch, SQL.
You have a solid understanding of Computer Science/Engineering fundamentals and first principles covering system design, data structures, architecture, and design patterns.
You have a Bachelor's degree in Computer Engineering / Science or Mathematics.About the team Join the innovation powerhouse - Content Enrichment team at Canva Our vision is to build the world's most enriched content data source to unlock a world class content & AI user experience.
We build models and human-in-the-loop workflows to enrich our content library so we impact Canva in four ways:Provide the vast majority of training data for any ML teams at Canva Fuel and improve AI features across Canva Enable more powerful public and private search experience Provide 360 view of Canva's content library so we can make data-driven content strategy decisions Finally, our crazy big goal is to build workflow to enable anyone at Canva to automatically generate, train and deploy classic ML models on top of our enriched content.
We're looking to grow the team to continue to scale the impact of machine learning across Canva. You'll be joining a fast moving cross-functional team, rapidly building and shipping machine learning-driven features to users and staff.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 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 youPlease note that interviews are conducted virtually.
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