Senior Machine Learning Engineer Agents data

At Canva our mission is to empower the world to design. Were building AI that feels magical and lands real impact for millions of people - helping anyone create with confidence. Were looking for a Machine Learning Engineer to own the data foundations that power our multimodal agent researchbuilding the pipelines datasets and tooling that turn ambitious research ideas into trainable reality.

About the team

We explore multimodal agentic architectures build scalable training and evaluation loops and partner closely with product and platform teams to turn breakthroughs into delightful product features. We are a cutting-edge post-training team developing new multimodal agentic systems. We work on all topics of multimodal modeling post-training and design agents we build scalable training and evaluation loops and partner closely with product and platform teams to turn breakthroughs into delightful product features.

About the role

Youll be responsible for the data lifecycle that fuels our agent research: from collection and curation through to preprocessing quality assurance and delivery into training pipelines. Youll work closely with research scientists to understand what data is needed then design and build the systems to make it happenreliably and at scale. Youll have significant autonomy over how data problems get solved while aligning on what problems matter most with the broader team.

What youll be doing in this role

• Design and build data pipelines for agent training: collection filtering deduplication formatting and versioning across text image and multimodal sources.

• Develop tooling for dataset constructionincluding human annotation workflows synthetic data generation and preference data collection for RLHF/DPO-style training.

• Own data quality: build validation frameworks monitor for drift and contamination and establish standards that make datasets trustworthy and reproducible.

• Create evaluation datasets and benchmarks in collaboration with researcherscurating task distributions that surface real failure modes.

• Build and maintain infrastructure for efficient data loading storage and retrieval at scale (S3 distributed systems streaming pipelines).

• Collaborate with research scientists to translate research requirements into concrete data specifications and iterate as experiments reveal new needs.

• Document datasets thoroughly: provenance known limitations intended use cases and versioning history.

• Profile and optimize research code for training and inference efficiency implement comprehensive test coverage for data pipelines and ML workflows ensuring reliability and catching regressions early.

• Elevate codebase quality through code reviews refactoring and establishing engineering best practices that help research velocity scale sustainably.

• Contribute to team roadmaps by identifying data bottlenecks and proposing solutions that unblock research velocity.

Youre likely a match if you have

• Strong software engineering skills in Python with experience building production-grade data pipelines and ML DevOps.

• Practical experience with prompt engineeringdesigning testing and refining prompts for reliable LLM/VLM outputs.

• Experience with ML data workflows: large-scale data processing and loading (Ray or similar) data versioning and format considerations for training (tokenization batching sharding).

• Hands-on experience working with data pipelines for large scale distributed ML training runs.

• Familiarity with annotation tooling and human-in-the-loop data collection (Label Studio or internal systems).

• Understanding of ML training requirementsyou know what good data looks like for LLM/VLM fine-tuning and can anticipate downstream issues.

• Experience loading and writing large datasets to/from cloud infrastructure (AWS) and distributed storage systems.

• Strong communication skills: you can work with researchers to scope ambiguous problems and translate needs into actionable plans.

• A collaborative approach comfortable taking ownership and iterating quickly.

Nice to have

• Experience with preference data collection for RLHF or reward modeling.

• Familiarity with multimodal data (image-text pairs video design assets).

• Experience building synthetic data generation pipelines using LLMs.

• Background in data quality metrics and monitoring systems.

• Contributions to dataset releases or benchmarks in the ML community.

Additional Information :

Whats in it for you

Achieving our crazy big goals motivates us to work hard - and we do - but youll experience lots of moments of magic connectivity and fun woven throughout life at Canva too. We also offer a stack of benefits to set you up for every success in and outside of work.

Heres a taste of whats on offer:

• 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 home office setup & more
• Flexible leave options that empower you to be a force for good take time to recharge and supports you personally

Check out  for more info.

Other stuff to know

We make hiring decisions based on your experience skills and passion as well as how you can enhance Canva and our culture. When you apply please tell us the pronouns you use and any reasonable adjustments you may need during the interview process.

Please note that interviews are predominantly conducted virtually. 

Remote Work :

Yes

Employment Type :

Full-time