Cartesia

Research Engineer, Audio Understanding

Full-time · *HQ - San Francisco, CA
✓ Verified live on the employer's own system · added 215 days ago
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Full job description

Data is one of the most critical inputs to frontier AI. In this role, you'll work across the full data stack - from infrastructure and web-scale data pipelines to modeling and evaluation. You'll develop a deep understanding of how data influences model performance and leverage that knowledge to advance the frontier of multimodal datasets to create new capabilities for AI.

- Design and build high-quality datasets for model training and run controlled modeling experiments to measure their impact on model performance and behavior.

- Engineer web-scale data pipelines and build systems to annotate and ensure data quality at scale.

- Develop techniques for post-training and synthetic data generation to improve model quality and intelligence.

- Experience building or working with large multilingual datasets

- Experience with generative models (speech, text, or multimodal).

- Ability to help guide human annotation and evaluation across multiple languages.

- Strong applied ML background with a focus on data-centric approaches.

- Excitement for building scalable systems that bridge research and production.

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This posting was published by Cartesia on their own careers system and is shown here with a direct link to apply there. Employers: for corrections or removal, contact jobs@veritahire.com.