North American distributor of Hisense TVs, appliances and air care products
Hisense USA is the Georgia-based North American arm of Hisense, bringing TVs, refrigerators, air conditioners and other appliances to US retail. Its job posts reveal an unusual split: logistics-heavy hiring focused on cutting freight costs, alongside video codec R&D work on H.266, AV1 and MPEG standards proposals. Finance is also driving Pillar Two compliance and tax digitalization on an SAP, Oracle and Databricks/Snowflake data stack.
Notable leadership hires: Pro Channel Director
Hisense USA Corporation, founded in 2001 and headquartered in Alpharetta, Georgia, is a subsidiary of the Qingdao-based Hisense group. It markets a full line of consumer electronics and home appliances in North America, including televisions, refrigerators, air conditioners, dehumidifiers, beverage coolers and freezers. The company sells through major national retailers and online channels. It employs 51–200 people, with hiring concentrated in the United States across logistics, engineering, sales, operations and support.
Hisense USA uses SAP ERP, Oracle, Salesforce, Power BI, Tableau, Azure, Microsoft Fabric, Databricks and Snowflake, plus SolidWorks, ANSYS and UG NX for engineering and C++ and Python for video codec work.
Yes. Logistics is the largest hiring area at Hisense USA, with roles tied to reducing logistics costs, optimizing the supply chain and ensuring order fulfillment, all based in the United States.
Hisense USA is headquartered in Alpharetta, Georgia, and operates as the North American subsidiary of Hisense, which is based in Qingdao, China.
Other companies in the same industry, closest in size
Hisense USA's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.