Integrate real-time text-to-speech with Sonic-3.6, Cartesia. Backed by General Catalyst, Index and Kleiner Perkins.
About the role
On the Audio Post-Training team, you’ll be building and improving the capabilities that define how the rest of the world interacts with our generative audio models. This team is where customer needs meet research, and covers the full spectrum of modeling from ideation through productionization.
What they're looking for
- Strong fundamentals in software engineering, machine learning, debugging complex systems, and the ability + desire to learn quickly
- Experience building and ensuring quality of large multilingual datasets
- Experience training and debugging generative models (speech, text, or multimodal), especially SFT, RL, synthetic data, and evaluation (both human and automated)
- Excitement about solving problems grounded in real customer needs, not just benchmarks
- Bonus points if you have native proficiency in other languages!
- Note: Cartesia participates in E-Verify and will provide the federal government with Form I-9 information to confirm employment eligibility after hire
More about this role
Our mission is to architect AI that learns from and interacts with the world like humans do.
We're pioneering the model architectures that will make this possible. Our founding team met as PhDs at the Stanford AI Lab, where we invented State Space Models or SSMs, a new primitive for training efficient, large-scale foundation models. Our team combines deep expertise in model innovation and systems engineering paired with a design-minded product engineering team to build and ship cutting edge models and experiences.
We're funded by leading investors at Index Ventures and Lightspeed Venture Partners, along with Factory, Conviction, A Star, General Catalyst, SV Angel, Databricks and others. We're fortunate to have the support of many amazing advisors, and 90+ angels across many industries, including the world's foremost experts in AI.
On the Audio Post-Training team, you’ll be building and improving the capabilities that define how the rest of the world interacts with our generative audio models. This team is where customer needs meet research, and covers the full spectrum of modeling from ideation through productionization. On any given day, you might design evaluations to reliably...
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