Senior Research Data Engineer (AI)

Location: Vienna, Austria

Company

Canva is a design platform developing AI products that help millions of people create with confidence.

What you will do

• Design and build data pipelines for collecting, filtering, deduplicating, formatting, and versioning text, image, and multimodal datasets.
• Build infrastructure for large-scale data loading, storage, and retrieval using AWS, S3, distributed systems, and streaming pipelines.
• Translate research requirements into data specifications and collaborate with research scientists on experiments and benchmarks.
• Develop dataset construction tooling, including human annotation workflows, synthetic data generation, and preference data collection for RLHF/DPO-style training.
• Build validation, monitoring, testing, and documentation systems to ensure dataset quality, provenance, reproducibility, and pipeline reliability.
• Identify data bottlenecks, improve code quality, and contribute solutions to research roadmaps.

Requirements

• Strong Python software engineering skills and experience building production-grade data pipelines and ML DevOps systems.
• Practical experience with prompt engineering for reliable LLM/VLM outputs.
• Experience with large-scale distributed ML data workflows, data versioning, tokenization, batching, and sharding.
• Experience with annotation tooling, human-in-the-loop data collection, and large datasets in AWS and distributed storage systems.
• Understanding of data requirements for LLM/VLM fine-tuning, along with strong communication and collaboration skills.
• Ability to take ownership of ambiguous data problems and iterate quickly with research teams.

Nice to have

• Experience with preference data collection for RLHF or reward modeling.
• Familiarity with multimodal data such as image-text pairs, video, and design assets.
• Experience building synthetic data generation pipelines with LLMs.
• Background in data quality metrics, monitoring systems, dataset releases, or ML benchmarks.

Culture & Benefits

• Full-time permanent employment.
• Choice in how and where to work within the available work arrangement.
• Collaboration with research, product, and platform teams.
• Virtual interviews.
• Reasonable adjustments are available during the interview process.