Deepgram

HQ
Ann Arbor, Michigan, USA
Total Offices: 2
90 Total Employees
Year Founded: 2015

Offices at Deepgram

Deepgram is headquartered in Ann Arbor, Michigan, USA and has 2 office locations.

Hybrid Workplace

Employees engage in a combination of remote and on-site work.

We currently have a hybrid business model with a nationally distributed workforce and two physical offices, one in Ann Arbor, MI and another in Burlingame, CA.

Typical time on-site: Flexible

U.S. Office Locations

HQ
Ann Arbor, Michigan, USA

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.

Burlingame, California, USA

1827 Murchison Drive, Burlingame, CA, United States, 94010

Search the 6 jobs at Deepgram

Recently posted jobs

5 Hours Ago
California, USA
Remote
Artificial Intelligence • Machine Learning • Natural Language Processing • Software
As a Solutions Engineer at Deepgram, you will create innovative AI solutions for customers, enhance the support experience, and collaborate with various teams. Your role involves problem-solving, building prototypes, and leveraging technology to drive business value in a client-focused environment.
5 Hours Ago
California, USA
Remote
Artificial Intelligence • Machine Learning • Natural Language Processing • Software
As an Enterprise Customer Success Manager at Deepgram, you will drive value for enterprise clients by aligning their business objectives with Deepgram's AI solutions. You'll manage relationships, ensure contract renewals, and leverage customer insights to identify growth opportunities.
11 Hours Ago
Ann Arbor, MI, USA
Remote
Artificial Intelligence • Machine Learning • Natural Language Processing • Software
As a Research Scientist at Deepgram, you will innovate and build advanced voice AI solutions, utilizing deep learning to train models that interpret speech and comprehend text. You will drive large-scale training, optimize models, and collaborate with product and engineering teams to deploy AI capabilities.