Research Staff, Data Science

Deepgram is currently looking for seasoned Data Scientists with demonstrated experience solving hard data problems while exploring research frontiers to join our Research Staff. Conversational audio presents incredibly rich scientific, engineering, and infrastructure challenges that are orders of magnitude harder than working with text. As a Member of the Research Staff, you will help us to build an industrial “data factory” that will be used to power the next generation of Voice AI systems - unlocking the creation of models that go beyond basic transcription and comprehension, capturing nuanced meanings in complex conversations, adapting robustly to diverse speech patterns, and generating empathic responses with human-like, contextualized speech. You will collaborate closely with our product, engineering, and data teams to build and deploy models in the most scalable voice API on the planet. We look forward to you bringing your expertise, sharing insights from your latest experiments, and collaborating with us to push the boundaries of AI and voice technology.

We are seeking Research Staff who:

See "unsolved" problems as opportunities to pioneer entirely new approaches

Can identify the one critical experiment that will validate or kill an idea in days, not months

Have the vision to scale successful proofs-of-concept 100x

Are obsessed with using AI to automate and amplify your own impact

If you find yourself energized rather than daunted by these expectations—if you're already thinking about five ideas to try while reading this—you might be the researcher we need. This role demands obsession with the problems, creativity in approach, and relentless drive toward elegant, scalable solutions. The technical challenges are immense, but the potential impact is transformative.

Drive high performance data acquisition, preparation and synthesis pipelines to generate data for the next generation of speech and language AI foundation models

Develop advanced characterizations of complex conversational audio utilizing a diverse toolkit of signals processing techniques and deep learning models

Collaborate with DataOps and Engineering to create automated systems which scale the ability of human annotators to label high value data and provide critical 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

Are obsessed with making sense out of complex and/or messy data

Enjoy building from the ground up and love to create new systems from scratch

Are passionate about AI and interested in leveraging data to solve hard problems

Are motivated by the prospect of scaling yourself using automation and AI models

Experience building data processing pipelines from a blank page and owning the entire data stack including data acquisition, characterization, cleaning, serving and transformation

Experience and expertise applying statistical methods and deep learning models to understand complex data

Strong communication skills and the ability to translate complex concepts in simple terms, depending on the target audience

Strong software engineering skills with particular emphasis on developing clean, modular code in Python and working with Pytorch

Background in Physics, Mechanical Engineering or Language Processing

Experience building models

Speech and audio experience

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