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Deepgram is looking to solve the problem of making voice interaction accessible to everyone by developing new paradigms for audio AI to overcome the challenges posed by audio data scarcity, diversity, and high dimensionality.

Requirements

• 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 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

Responsibilities

• 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

Other

• Strong communication skills and the ability to translate complex concepts in simple terms, depending on the target audience
• Ability to work collaboratively with product, engineering, and data teams
• Obsession with making sense out of complex and/or messy data
• Motivation by the prospect of scaling yourself using automation and AI models
• Ability to provide accommodations for applicants who need them