Senior Machine Learning Engineer - Content Enrichment

Summary

Join Canva's team and redefine the world's design experience. Based in ANZ, this Machine Learning Engineer role focuses on building enrichment solutions to tag and classify content, designing data pipelines for metadata automation, and developing ML models for tasks like style transfer. You will troubleshoot technical issues, propose cost-reduction methods, manage stakeholders, and collaborate across teams. The team is responsible for Content Understanding and Concept Services and values collaboration and knowledge sharing. This role requires extensive experience in ML model development, particularly in computer vision, proficiency in PyTorch and cloud ML infrastructure, and familiarity with LLMs and prompt engineering.

Requirements

• You have more than 5 years of hands-on experience in designing and developing complex ML models, especially in computer vision
• You are experienced in R&D and conducting literature reviews on the latest ML techniques
• You are proficient in PyTorch and setting up cloud ML infrastructure, with familiarity in LLMs and prompt engineering as a must
• You are familiar with embeddings and vector databases
• You have experience working with microservices and large monorepos
• You follow disciplined coding practices, actively participate in code reviews, and set best-practice standards for your peers
• You possess strong written and verbal communication skills and excel in team collaboration
• As a Canva engineer, you take the time to fully understand the problem before diving into code

Responsibilities

• Building enrichment solutions to tag and classify a variety of content types in Canva's library
• Designing data pipelines to automate metadata backfills for the existing content library
• Wrangling datasets to train and evaluate ML models
• Troubleshooting and resolving technical issues within the team’s domain
• Designing and building bespoke ML solutions for novel problems such as style transfer and agentic design generation
• Proposing methods to decrease the cost of inference in our enrichment pipeline
• Managing stakeholders and identifying cross-team collaboration opportunities to drive new ideas and improvements that align with our goals
• Investigating and providing guidance on interacting with our service and codebase in response to stakeholder requests

Preferred Qualifications

• You hold a Master’s or PhD degree in a machine learning discipline
• You have experience with Ray, Weights & Biases, Kubernetes, and Java
• You have experience hosting LLM architectures and fine-tuning them through reinforcement learning

Benefits

• 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