Research Staff, Data Science

Stack

Responsibilities

• ▹Drive high-performance data acquisition, preparation, and synthesis pipelines for next-generation speech and language AI foundation models
• ▹Develop advanced characterizations of complex conversational audio using a diverse toolkit of signal processing techniques and deep learning models
• ▹Collaborate with DataOps and Engineering to build automated systems that scale human annotators' work and provide feedback on model outputs
• ▹Build advanced benchmarking methodologies and curated datasets for evaluating conversational voice systems
• ▹Document and present results of data experiments and analysis for internal and external audiences

Requirements

• ▹Experience building data processing pipelines from a blank page, owning the entire data stack: acquisition, characterization, cleaning, serving, and transformation
• ▹Experience and expertise applying statistical methods and deep learning models to understand complex data
• ▹Strong communication skills, able to translate complex concepts into simple terms depending on the audience
• ▹Strong software engineering skills, particularly writing clean, modular code in Python and working with PyTorch

Nice to have

• ▹Background in Physics, Mechanical Engineering, or Language Processing
• ▹Experience building models
• ▹Speech and audio experience

Soft skills

About the company

Deepgram is the leading platform in the fast-growing, trillion-dollar Voice AI economy, providing real-time speech-to-text (STT) and text-to-speech (TTS) APIs and production-grade voice agents. More than 200,000 developers and 1,300+ organizations build on it, including Twilio, Cloudflare, and Sierra; backed by a recent Series C round, the company has processed over 50,000 years of audio to date.