Senior ML Research Scientist (Speech)
Rad AI- Full Time
- Senior (5 to 8 years)
Deepgram is the leading voice AI platform for developers building speech-to-text (STT), text-to-speech (TTS) and full speech-to-speech (STS) offerings. 200,000+ developers build with Deepgram’s voice-native foundational models – accessed through APIs or as self-managed software – due to our unmatched accuracy, latency and pricing. Customers include software companies building voice products, co-sell partners working with large enterprises, and enterprises solving internal voice AI use cases. The company ended 2024 cash-flow positive with 400+ enterprise customers, 3.3x annual usage growth across the past 4 years, over 50,000 years of audio processed and over 1 trillion words transcribed. There is no organization in the world that understands voice better than Deepgram.
Voice is the most natural modality for human interaction with machines. However, current sequence modeling paradigms based on jointly scaling model and data cannot deliver voice AI capable of universal human interaction. The challenges are rooted in fundamental data problems posed by audio: real-world audio data is scarce and enormously diverse, spanning a vast space of voices, speaking styles, and acoustic conditions. Even if billions of hours of audio were accessible, its inherent high dimensionality creates computational and storage costs that make training and deployment prohibitively expensive at world scale. We believe that entirely new paradigms for audio AI are needed to overcome these challenges and make voice interaction accessible to everyone.
Speech recognition APIs for audio transcription
Deepgram specializes in artificial intelligence for speech recognition, offering a set of APIs that developers can use to transcribe and understand audio content. Their technology allows clients, ranging from startups to large organizations like NASA, to process millions of audio minutes daily. Deepgram's APIs are designed to be fast, accurate, scalable, and cost-effective, making them suitable for businesses needing to handle large volumes of audio data. The company operates on a pay-per-use model, where clients are charged based on the amount of audio they transcribe, allowing Deepgram to grow its revenue alongside client usage. With a focus on the high-growth market of speech recognition, Deepgram is positioned for future success.