Company: Qualcomm China Job Area:Engineering Group, Engineering Group Machine Learning Engineering General Summary: About us: We are Qualcomm AI Research that are advancing AI to make its core capabilities – perception, reasoning, and action – ubiquitous
WeRide is a smart mobility start-up whose mission is to transform mobility with autonomous driving. We are committed to build better transportation experience that’s safe, efficient, affordable and joyful. We have an elite team of entrepreneurs
Responsibilities: Be responsible for one or more LSEG Software Systems design, development and support. Work with Project Managers and/or Product Manager to ensure the delivery of high quality software on time. Working with Product team and
Tätigkeitsbereich:Forschung & Entwicklung incl. Design Fachabteilung:Advanced Design Center China Gesellschaft:Mercedes-Benz Group China Ltd. Standort:Mercedes-Benz Group China Ltd., Beijing Startdatum:31.07.2026 Veröffentlichungsdatum:07.07.2026 Stellennummer:MER00045AN Arbeitszeit:Vollzeit Bewerben Aufgaben China is Mercedes-Benz’s largest passenger car market globally. At Mercedes-Benz R&D China,
Overview About the Role & Team The role is to help accelerate artificial intelligence adoption, automation, and digital transformation across Devices analyst team. This role will bridge business needs and practical technology, especially will identify repeatable
About Analog Devices Analog Devices, Inc. (NASDAQ: ADI) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, AI, and software technologies into
Back-end Software Engineer WirelessCars Journey WirelessCar empowers the future of mobility by connecting vehicles and delivering cutting-edge digital services. Founded in 1999 and headquartered in Sweden, we have a strong global presence with offices in the
Trexquant is a systematic hedge fund where we use thousands of statistical algorithms to trade equity, futures and other markets globally. Starting with many data sets, we develop large sets of features and use various machine learning