Superhuman
Superhuman Offices
Superhuman is headquartered in San Francisco and has 3 office locations.
Hybrid Workplace
Employees engage in a combination of remote and on-site work.
Typical time on-site:
Flexible
U.S. Office Locations
San Francisco
Grammarly’s San Francisco headquarters is located downtown, just a 5-minute walk from the Embarcadero BART station.
New York
450 Park Ave South, New York, NY, United States, 10016
Seattle
4311 11th Ave NE , Seattle, WA, United States, 91805
Recently posted jobs
Artificial Intelligence • Information Technology • Machine Learning • Natural Language Processing • Productivity • Software • Generative AI
The Staff Brand Writer will create brand and product narratives across campaigns, launches, and user touchpoints. Responsibilities include translating complex AI capabilities into clear language, shaping content strategy, partnering cross-functionally with Product, Engineering, Marketing, Legal, Design, and Research, managing multiple projects, advocating for users through insights and data, maintaining high writing standards, and mentoring other writers.
Artificial Intelligence • Information Technology • Machine Learning • Natural Language Processing • Productivity • Software • Generative AI
Design, build, and operate large-scale ETL pipelines, data lakes, and data platforms processing billions of daily events. Own data quality, freshness, reliability, monitoring, and observability for foundational datasets. Develop self-service ETL frameworks and tooling, contribute to architecture and technical strategy, and partner with product, engineering, machine learning, data science, and leadership teams to deliver scalable data solutions.
Artificial Intelligence • Information Technology • Machine Learning • Natural Language Processing • Productivity • Software • Generative AI
Build and operate scalable growth data pipelines, models, feature datasets, and measurement systems supporting paid acquisition, ad bidding, experimentation, attribution, and audience targeting. Partner with Growth, Marketing, Analytics Engineering, and Data Science to deliver reliable data products, productionize machine-learning workflows, maintain data quality and observability, and improve platform performance, cost efficiency, and developer experience.
