6 days ago

Senior Research Scientist - Design Generation (Sydney)

Canva

Sydney

6 days ago

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Canva is seeking a Senior Research Scientist to join the Design Generation team in Sydney, working on generative models for AI-assisted design. The role involves training and evaluating generative models at scale, with a focus on LLMs and multimodal models. Candidates should have a PhD in AI/ML with at least 2 years of industry experience, or 6+ years without a PhD.

Core AIOn-siteFull-timeSeniorLarge Language ModelsMultimodal Models

Senior Research Scientist - Design Generation (Sydney)

Apply

Core AIOn-siteFull-timeSeniorLarge Language Models

Salary

Not specified

Work Location

Sydney, New South Wales, Australia, AU

Work Model

On-site

Experience Required

6 years

Employment Type

Full-time

Experience Level

Senior

Core Qualifications

Technical (Must-have)

Large Language ModelsMultimodal ModelsGenerative ModelsFine-tuningData PipelinesMulti-GPU TrainingMachine LearningDeep LearningDiffusion ModelsImage GenerationEvaluation MethodsBenchmarking

Soft Skills

AutonomyCommunicationCuriosityJudgmentPassionWillingness to Learn

Preferred Qualifications

Technical (Nice-to-have)

Diffusion ModelsImage Generation

Key Responsibilities

•Train and evaluate generative models like LLMs for design generation
•Design and run experiments to test hypotheses about model architecture, training approach, and data
•Build and improve evaluation methods and benchmarks for measuring generative design quality
•Translate research findings into techniques and approaches the team can move toward production
•Investigate model quality issues, failure modes, and gaps against user and business needs
•Stay current with generative modelling research and bring relevant advances into the team's work
•Communicate research findings and trade-offs clearly, including to non-research stakeholders, and share knowledge across the team

Research ScientistGenerative AIMachine LearningLLMMultimodalDesign GenerationSydneyFull-timeOn-site

Key Responsibilities

•Train and evaluate generative models like LLMs for design generation

•Design and run experiments to test hypotheses about model architecture, training approach, and data

•Build and improve evaluation methods and benchmarks for measuring generative design quality

•Translate research findings into techniques and approaches the team can move toward production

•Investigate model quality issues, failure modes, and gaps against user and business needs

•Stay current with generative modelling research and bring relevant advances into the team's work

•Communicate research findings and trade-offs clearly, including to non-research stakeholders, and share knowledge across the team