Grammarly

HQ
San Francisco, CA, US
Total Offices: 7
900 Total Employees
Year Founded: 2009
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Offices at Grammarly

Grammarly is headquartered in San Francisco, CA and has 7 office locations.

Hybrid Workplace

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

Typical time on-site: Flexible

U.S. Office Locations

HQ San Francisco, CA, US New York, NY, US Seattle, WA, US

Global Office Locations

Berlin, DE Kiev, UA Kraków, PL Vancouver, BC, CA
HQ
San Francisco, CA, US

Grammarly’s San Francisco headquarters is located downtown, just a 5-minute walk from the Embarcadero BART station.

Jobs At This Office
Berlin, DE

Pressehaus Podium Karl-Liebknecht-Straße 29A , Berlin, Germany, 10178

Kiev, UA

Gulliver, Sportyvna Square, 1A, , Kiev, Ukraine, 01601

Kraków, PL
Krakow

Podium Park, aleja Jana Pawła II 43b, , Kraków, Poland, 31-864

New York, NY, US

450 Park Ave South, New York, NY, United States, 10016

Seattle, WA, US
Seattle

4311 11th Ave NE , Seattle, WA, United States, 91805

Vancouver, BC, CA

353 Water Street , Vancouver, BC, Canada, V6B 1B8

Search the 64 jobs at Grammarly

Recently posted jobs

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Artificial Intelligence • Information Technology • Machine Learning • Natural Language Processing • Productivity • Software • Generative AI
The Machine Learning Engineer will work on NLP projects for Grammarly's Enterprise team, focusing on building AI products and capabilities that enhance communication in organizations. The role involves applying ML technologies, collaborating with cross-functional teams, and innovating to solve technical challenges at scale.
Artificial Intelligence • Information Technology • Machine Learning • Natural Language Processing • Productivity • Software • Generative AI
As a Software Engineer for Windows at Grammarly, you will develop enhancements for the Windows application, focusing on performance, quality, and desktop integrations. Your role includes creating a robust architecture, optimizing for performance, and utilizing C#, .NET, and WPF to innovate and solve technical challenges.
Artificial Intelligence • Information Technology • Machine Learning • Natural Language Processing • Productivity • Software • Generative AI
Lead a high-performing team to build graphs of data about Enterprise customers. Collaborate with various teams to develop systems using cutting-edge technologies like LLMs and graph databases. Drive the development of a knowledge graph integrated with analysis and ranking systems while ensuring responsible data usage.
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