Deepgram
Deepgram Offices
Deepgram is headquartered in San Francisco and has 2 office locations.
Remote Workplace
Employees work remotely.
U.S. Office Locations
San Francisco
548 Market St., San Francisco, CA, United States, 94104
Ann Arbor
While most of our employees work out of their homes across the US, a small group works out of our Ann Arbor Office. Centrally located in a fantastic college town, this office is tight-knit and takes advantage of the numerous restaurants and bars in the area.
Recently posted jobs
Artificial Intelligence • Machine Learning • Natural Language Processing • Software • Conversational AI
Leads internal communications for a rapidly scaling, distributed technology company. Builds communication systems, channels, and cadences; partners with executives on employee messaging; translates complex business and technical information; supports culture, employee experience, company narrative, and major company moments; and uses data and AI to improve communication effectiveness.
Artificial Intelligence • Machine Learning • Natural Language Processing • Software • Conversational AI
Lead brand campaign concepting and copywriting across OOH, audio, video, social, events, web, launches, and other brand surfaces. Own Deepgram’s verbal identity, review agency and studio copy, translate technical products for varied audiences, contribute to naming, and develop scalable copy guidelines and workflows. The role also emphasizes AI-forward writing tools, collaboration with design and marketing teams, global adaptation, and maintaining a distinctive, clear brand voice.
Artificial Intelligence • Machine Learning • Natural Language Processing • Software • Conversational AI
Research Staff will develop foundational voice AI technologies, including neural audio codecs, steerable generative models, latent-space embeddings, synthetic audio data generation, multimodal speech-to-speech systems, and hardware-efficient architectures. The role combines mathematical modeling, algorithmic innovation, large-scale data engineering, real-time deployment optimization, and rigorous experimental design to advance scalable, low-latency voice interaction.
