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Building AI data pipelines for agent training and evaluation datasets at a design tech company. Production-grade data pipeline and ML DevOps experience required. Choice in work location and method.
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Anforderungen
- Strong software engineering skills in Python
- Experience building production-grade data pipelines
- ML DevOps experience
- Practical prompt engineering experience
- Designing, testing, refining prompts for LLM/VLM outputs
- Experience with ML data workflows
- Large-scale data processing and loading
- Data versioning
- Format considerations for training
- Hands-on experience with data pipelines for large-scale distributed ML training
- Familiarity with annotation tooling
- Familiarity with human-in-the-loop data collection
- Understanding of ML training requirements
- Knowledge of good data for LLM/VLM fine-tuning
- Anticipation of downstream issues
- Experience loading/writing large datasets to/from cloud infrastructure
- Experience loading/writing large datasets to/from distributed storage systems
- Strong communication skills
- Ability to work with researchers to scope problems
- Ability to translate needs into actionable plans
- Collaborative approach
- Comfortable taking ownership
- Comfortable iterating quickly
- Experience with preference data collection for RLHF
- Experience with reward modelling
- Familiarity with multimodal data
- Experience building synthetic data generation pipelines using LLMs
- Background in data quality metrics
- Background in monitoring systems
- Contributions to dataset releases or benchmarks
Aufgaben
- Design and build data pipelines for agent training
- Build and maintain infrastructure for data loading, storage, and retrieval
- Collaborate with research scientists to translate research requirements into data specifications
- Create evaluation datasets and benchmarks with researchers
- Develop tooling for dataset construction
- Own data quality by building validation frameworks and monitoring for drift
- Document datasets thoroughly
- Implement comprehensive test coverage for data pipelines and ML workflows
- Elevate codebase quality through code reviews and refactoring
- Contribute to team roadmaps by identifying data bottlenecks and proposing solutions
Berufserfahrung
Ausbildung
Sprachen
Tools & Technologien
Benefits
- Choice in work location
- Choice in work method
- Trust in employee autonomy
Von Nejo automatisch aufbereitet
Nejo hat diesen Job automatisch von der Website des Unternehmens Canva erfasst und die Informationen auf Nejo mit Hilfe von KI für dich aufbereitet. Trotz sorgfältiger Analyse können einzelne Informationen unvollständig oder ungenau sein. Bitte prüfe immer alle Angaben in der Originalanzeige! Inhalte und Urheberrechte der Originalanzeige liegen beim ausschreibenden Unternehmen.
Zur Originalanzeige bei CanvaÜber das Unternehmen
The company is a fast-growing platform that redefines how the world experiences design.
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