Applied Researcher, Audio Post-Training
CartesiaVoice AI company
San Francisco, United StatesSenior
Index Ventures
Kleiner Perkins
Lightspeed Venture Partners
General Catalyst
NVIDIA
A* Capital
Data & AI
About the role
TL;DR
Develop and improve generative audio models for customer interaction.
- •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.
- •Key Responsibilities Collaborate with product teams to understand and prioritize customer asks Cut through the ambiguity of vaguely described behavioral problems to make concrete research plans.
- •Ideate and experiment across the full modeling stack, including data processing, synthetic data, SFT, RL, and evals to solve for high priority model capabilities Root cause failures in production models and understand how to fix them in future model iterations Decide which features and capabilities are ready for public launch Requirements 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!
Required skills
PythonTensorFlowscikit-learn
Domain expertise
ai
Benefits & perks
Compensation, Health Insurance, Parental Leave, 401(k), Commuter Allowance, Flexible PTO, Meals & Snacks
Tech stack
PythonTensorFlowPyTorchscikit-learnKubernetesCI/CD