2027 Campus - Automotive Applications Engineer - Processors
Requirements at a glance
2027 Campus - Automotive Applications Engineer - Processors at Nxp is a role based in Chongqing. The posting mentions a master's degree. It does not mention visa sponsorship. Key skills include C++ and C. Applications are submitted through Workday.
- Education
- Master's degree (mentioned)
- Visa sponsorship
- Not mentioned in the posting
- Application platform
- Workday
Skills in this posting
- C++
- C
- Linux
- Machine learning
Highlighted skills appear in the posting's requirements.
Extracted automatically from the job description. Confirm details in the full posting below.
Job Responsibilities
- Deliver technical support to customers adopting NXP automotive processors and system solutions.
- Develop, validate, and optimize application software and reference designs for automotive processor-based systems.
- Collaborate with global NXP teams to support successful New Product Introduction and customer enablement.
Qualifications
- Master's degree in Electronic Engineering, Computer Science, Software Engineering, Communication Engineering, Automation, Automotive Engineering, or a related field.
- Strong willingness and ability to learn new technologies, tools, and customer requirements quickly.
- Fluent verbal and written English communication skills, with a responsive, proactive, and collaborative attitude.
- Experience with microcontroller or microprocessor architectures, such as ARM-based platforms, and C/C++ application development.
- Familiarity with networking technologies and protocols, including CAN, Ethernet, TCP/IP, routers, and switches.
- Ability to perform basic hardware debugging using tools such as oscilloscopes, logic analyzers and multimeters.
Preferred Qualifications
Candidates who meet one or more of the following criteria will be highly preferred:
Experience with embedded platform software, including RTOS, embedded Linux, BSPs, kernel-level concepts, and device driver development.
Knowledge of automotive ECU architectures and systems, including central computing platforms, zonal controllers, domain controllers, and vehicle gateways.
Exposure to AI-related technologies, such as machine learning frameworks, edge AI deployment, neural network acceleration, or AI-enabled automotive applications.