Palantir Technologies Offices

Palantir Technologies is headquartered in United States and has 10 office locations.

OnSite Workplace

Employees work from physical offices.

Typical time on-site: 5 days a week

U.S. Office Locations

Global Office Locations

HQ
United States

Miami, FL

United States

Japan

Tokyo

South Korea

Seoul

Spain

Madrid

United Kingdom

London

United Kingdom

United States

New York City, NY

United States

United States

Washington, DC

United States

United States

Palo Alto, CA

United States

United States

Seattle, WA

United States

United States

Chicago

United States

2 Days AgoSaved
Hybrid
London, Greater London, England, GBR
Artificial Intelligence • Software
Build and improve data-processing infrastructure and query engines supporting Palantir Foundry. Responsibilities include optimizing query plans, developing execution capabilities, improving large-table performance, and contributing across design, coding, testing, code review, and releases. The role involves working with distributed systems, databases, compilers, operating systems, open-source technologies, and multiple programming languages while prioritizing correctness, compatibility, and performance.
2 Days AgoSaved
In-Office
New York, NY, USA
Artificial Intelligence • Software
Work on query engines and data-processing infrastructure powering Palantir Foundry. Responsibilities include optimizing query plans, developing execution-engine capabilities, improving large-table performance, and contributing through design, coding, testing, code review, and release. The role involves working with technologies such as Spark, DataFusion, Iceberg, Arrow, and Parquet while learning how modern distributed data systems operate.
2 Days AgoSaved
Hybrid
New York, NY, USA
Artificial Intelligence • Software
Build and improve data processing infrastructure and query engines supporting Palantir Foundry. Develop query planning rules, native execution capabilities, and large-table performance improvements using technologies such as Apache Spark, DataFusion, Iceberg, Arrow, and Parquet. Contribute across design, coding, testing, code review, and release while emphasizing correctness, compatibility, and predictable performance.