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
Build AI-powered workflows, agents, integrations, and internal tools that automate People Operations. Partner with People, Engineering, and IT to modernize onboarding and other employee processes, while implementing secure access controls, human oversight, escalation paths, and production-ready architectures. Prototype with users, iterate quickly, and measure improvements in efficiency, employee experience, and operational consistency.
Artificial Intelligence • Machine Learning • Natural Language Processing • Software • Conversational AI
Lead Deepgram’s corporate legal function, including governance, IPO readiness, financings, M&A, employee equity, international subsidiaries, and regulatory developments. Partner with Finance, People, and company leadership to build scalable legal processes for a fast-growing AI company. Establish an AI-native legal practice while advising on a broad range of startup legal matters.
Artificial Intelligence • Machine Learning • Natural Language Processing • Software • Conversational AI
Own the company’s metric registry and canonical definitions, resolve conflicting metrics, enforce definitions in semantic and catalog systems, and retire redundant reporting assets. Build data quality checks, route failures to accountable owners, and evaluate AI agents against ground truth. Enable trustworthy self-service analytics through governed data. The role requires strong SQL, production ownership of a semantic or metrics layer, data catalog or lineage experience, clear documentation, and cross-functional decision-making.
