Applied Researcher, Audio Post-Training
$200,000–$350,000 year
On-siteSan Francisco, California, United States
Job Summary
Design evaluations to measure generative audio capabilities, build processing pipelines to improve data quality, and experiment with finetuning and reinforcement learning approaches to refine model behavior. Synthesize customer complaints into holistic understanding of capability gaps, driving research efforts across data, model training, and evaluation to close those gaps. Root cause failures in production models and decide which features are ready for public launch while collaborating with product teams to prioritize customer asks. This role requires broad research experience with end-to-end ownership, combining software engineering fundamentals with debugging complex systems to solve problems grounded in real customer needs.
Required Qualifications
- 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).
Desired Qualifications
- Bonus points if you have native proficiency in other languages!
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