Cartesia is looking to build the next generation of AI that can continuously process and reason over massive multimodal data streams (audio, video, text) on-device. This requires building and managing large-scale, high-quality multimodal datasets to power their cutting-edge research and foundational models.
Requirements
- Technical expertise in large-scale data engineering.
- Familiarity with building datasets for and evaluating generative models.
Responsibilities
- Define Cartesia’s overall multi-modal data strategy across pre-training and post-training, including human, synthetic, and web-scale data sources.
- Design and oversee the construction of robust, scalable data pipelines for text, audio, and video.
- Establish and enforce rigorous standards for data quality across the organization.
- Deeply understand how data affects model capability and proactively identify and source novel datasets.
Other
- Lead, manage, and mentor a team.
- Manage relationships and budgets with external data vendors and partners.
- Leadership skills to grow and guide a high-impact data team.
- We’re an in-person team based out of San Francisco.
- Relocation and immigration support.
