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Staff Machine Learning Engineer – Recommendations
CanvaStaff Machine Learning Engineer in the Recommendations team at Canva, delivering personalized recommendations using advanced ML techniques. Lead design, implementation, and improvement of machine learning models.
Tech Stack
Tools & technologiesNumpyPandasPythonPyTorchScikit-Learn
About the role
Key responsibilities & impact- You'll design, implement, and refine machine learning models to deliver personalized recommendations, taking on the most complex and ambiguous parts of the system.
- You'll improve the architecture, code structure, and performance of our machine learning systems, helping raise the engineering quality bar across the team.
- You'll investigate research papers and state-of-the-art machine learning models, and judge which ones are worth bringing into production at Canva.
- You'll lead the design of online and offline experiments to validate model performance, and make data-driven calls on what to ship and what to iterate on.
- You'll shape how our machine learning models integrate with the broader technology stack, ensuring strong performance and reliability across the pipeline.
- You'll work closely with product and engineering teams to deploy new recommendation features, driving alignment when initiatives span multiple teams.
- You'll document and communicate your work to both technical and non-technical stakeholders — including senior leadership — and mentor MLEs around you through reviews, pairing, and shared knowledge.
Requirements
What you’ll need- Significant experience developing, shipping, and operating production-scale recommendation systems.
- Proficiency in Python and core ML tooling (PyTorch, pandas, scikit-learn, numpy), with strong fluency on the engineering side of ML — training pipelines, evaluation, and serving.
- Strong analytical skills, with a track record of rigorously evaluating model performance and making data-driven calls on what to ship and what to iterate on.
- Excellent communication skills, with the ability to explain complex technical concepts to a wide range of audiences — including senior leadership.
- A collaborative mindset and a passion for working with cross-functional teams to achieve shared goals, including supporting the growth of MLEs around you.
Benefits
Comp & perks- 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
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Machine Learning Model DevelopmentModel EvaluationTraining PipelinesModel ServingData-Driven Decision Making
Soft Skills
Excellent CommunicationCollaborative MindsetMentorship