Senior Machine Learning Engineer (Search) - Remote across ANZ
Sydney, New South Wales, Australia
At Canva, we celebrate diversity. We deeply believe that bringing together diversity of thoughts, perspectives and expression is key to building the best product, team and company. We look for many different skills and abilities, as well as how you can enhance Canva and our culture. So, even if you don’t think you quite meet all of the skills listed or tick all the boxes, we’d still love to hear from you!
Our mission at Canva is to empower the world to design and since launching in 2013, we have grown exponentially, amassing over 86 million monthly active users across 190 different countries and a team of over 3,000 people… and the best bit is that we’ve only achieved 1% of what we know we’re capable of.
Join us and design your future.
The Machine Learning Engineering specialty is engaged in delivering value to Canva’s users, by designing, building and maintaining complex production systems to apply statistics and machine learning at scale. We're building a highly personalised Canva; developing and productionising user modelling that directly drives product features and targeting messaging and marketing; making it easy for users to discover over 100M+ templates, photos, videos and elements; applying ML to label and transform a vast number and variety of images; and leveraging our unique design data to empower users to design.
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.
The Search & Recommendations Group is working to enhance its search retrieval and relevance capabilities. We are expanding our use of ML-based approaches as we continue to scale up across languages and markets, design content types, and creator marketplace contributions.
The core technical pieces to support these capabilities include:
- Indexing - Visual content representation and content understanding
- Retrieval - Query understanding, language understanding
- Ranking - Topical, contextual, personalised and business objective feature modelling and ranking systems
- User experience - Universal search systems, diversity-aware ranking
- Query assistance - Autocomplete, popular and related searches
- Metrics and experimentation - Development of sensitive offline and online metrics and more efficient and predictive experimentation systems.
Responsibilities
- Working in one or more of the search layer areas listed above
- Applying knowledge of information retrieval technologies, e.g., OpenSearch, ElasticSearch, Solr, Learning to Rank algorithms and toolkits
- Building scalable ML solutions that meet our SLA guidelines, beyond just ML model training
- Model deployments and feature engineering as part of large-scale systems using a service-oriented architecture
- Analytical skills with hypothesis-driven problem solving and turning data into actionable insights
- Practical and ethical considerations of ML data sets for training and evaluation
Background
- Requirement to have worked in search, ranking, ads, etc.
- Good knowledge in one or more of the following areas: machine learning, learning to rank, information retrieval, search-specific experimentation and metrics.
- (Ideal) Experience at working in hyper-growth companies that incorporate search or recommendations as part of a product experience (high growth teams, rapidly evolving requirements, and building E2E ranking systems)
- (Ideal) Specific image/video search experience and/or image/video understanding and feature representation via state-of-the-art models.
- (Bonus) Interest & experience in responsible AI considerations with ML-based systems.
If you require visa sponsorship, you must ensure you have at least two (2) years of post-University commercial experience as a Software Engineer and meet the mandatory sponsorship requirements laid out by Department of Home Affairs.
We will not accept or review any CVs from external recruitment agencies.
Working at Canva
Our culture is unlike anywhere else and we design your #CanvaLife experience to empower you to do the best work of your life.
Whether you’re in the office, working from home or choosing your own adventure, our benefits for permanent Canvanauts include:
• Equity packages for you to truly be a part of the Canva journey. • We have a hybrid work model (in-office & from home), so while our offices are always open to you, we aim to come together for 8 days a year at minimum - balancing flexibility and connection • Flexible leave so you can recharge, give back, support others or focus on your own professional development. • Inclusive parental leave policy that supports all parents and carers throughout their parenting and caring journey. • An annual Vibe & Thrive allowance. This is for you to spend on whatever will support your wellbeing and development.. because you know what you need to Vibe and Thrive, better than anyone. • Virtual and in-office wellness benefits including Canva University, Employee Assistant Programs and Fitness & Meditation Classes. • Canva For Good program matching your not-for-profit donations, Force for Good leave (3 paid volunteering days) and a range of sustainability and ethical initiatives to get involved in.
We make hiring decisions based on your experience, skills and passion. Please note that interviews are conducted virtually. When you apply, please tell us the pronouns you use and any reasonable adjustments you may need during the interview process.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Elasticsearch Engineering Feature engineering Machine Learning Model training Nonprofit Statistics
Perks/benefits: Career development Fitness / gym Flex hours Home office stipend Parental leave Salary bonus Startup environment Wellness
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