Machine Learning Engineer - International SG (AI)

TL;DR

Machine Learning Engineer (AI): Developing and adapting search, recommendation, and AI Magic experiences for the Chinese market with an accent on local model fine-tuning and regulatory compliance. Focus on building data pipelines, prompt engineering, and running online experiments to improve the user journey in priority international markets.

Location: Beijing, China

Company

Canva is a global visual communication platform focused on empowering the world to design.

What you will do

• Develop and adapt AI models (LLMs, image/video generation, Rec Systems) to support product needs in China.
• Perform fine-tuning and prompt engineering of models using localized datasets and usage signals.
• Build and maintain scalable, region-compliant data pipelines and model-serving components.
• Collaborate with global and local teams across ML, product, infra, legal, and compliance.
• Run offline evaluations and support online experimentation to measure model performance and user impact.
• Contribute to technical discussions and share learnings with the broader AI teams.

Requirements

• 1–3 years of ML or software engineering experience.
• Proficiency in Python and ML frameworks like PyTorch, TensorFlow, or Hugging Face.
• Familiarity with production ML areas such as LLMs, search, recommendation, or generative AI.
• Foundational understanding of fine-tuning, prompt engineering, data processing, and model evaluation.
• Strong communication and collaboration skills for working across distributed teams.
• Must be based in Beijing, China.

Nice to have

• Exposure to or interest in Chinese AI models, vendors, or datasets.
• Experience with cloud platforms or ML infrastructure, including containerization and GPU serving.
• A product mindset and curiosity about solving real user problems with AI.

Culture & Benefits

• Opportunity to deepen experience in building agentic conversational AI systems.
• Direct contribution to high-impact initiatives supporting a mission of 1B users.
• Mentorship opportunities within the ML community and growth of cross-functional influence.
• Ability to shape the future of ML-powered user interaction and automation.