Embedded Machine Learning & Radar Processing Intern - Summer 2027

Location: San Jose (Holger Way)

Time Type: Full time

Job Description

Join NXP's Innovation R&D team in the heart of Silicon Valley and help shape the future of automotive radar, AI, and autonomous perception systems. As an intern, you will work alongside industry experts developing next-generation radar technologies that power advanced driver assistance and self-driving vehicles.

In this role, you will:

• Contribute to cutting-edge automotive radar and perception solutions that push the boundaries of vehicle intelligence.
• Apply hands-on software engineering skills using custom IDEs, compilers, SDKs, and toolchains targeting advanced edge AI SoCs.
• Benchmark and optimize AI/ML models on NXP hardware platforms, gaining firsthand experience with real-world edge AI deployment.
• Build and enhance the software stack required to deliver a full radar system proof-of-concept (PoC), from machine learning models to embedded deployment.
• Collaborate with multidisciplinary teams spanning AI, signal processing, embedded systems, and semiconductor hardware.

Preferred Qualifications

Machine Learning & AI Experience

• Strong hands-on experience with machine learning and deep learning development.
• Proficiency in Python and modern ML frameworks such as PyTorch and TensorFlow.
• Experience optimizing and deploying AI models on resource-constrained embedded platforms.
• Bonus: Experience with custom AI toolchains such as NXP eIQ Auto.
• Bonus: Experience with model quantization, acceleration, or performance optimization for edge devices.

Embedded Software Experience

• Strong programming skills in C, C++, and Embedded C.
• Experience setting up and using embedded development environments, including IDEs, compilers (GCC), and debuggers (GDB).
• Experience with embedded Linux software development and system integration.
• Familiarity with Hardware-in-the-Loop (HIL) testing and embedded software development using custom APIs.
• Experience with Robot Operating System (ROS/ROS2).
• Bonus: Experience with FPGA-based emulation platforms, hardware accelerators, or cycle-accurate simulators.
• Bonus: Familiarity with AI accelerators, NPUs, DSPs, or heterogeneous computing architectures.

Additional Qualifications

• Excellent communication, technical writing, and presentation skills.
• Self-driven, highly motivated, and passionate about solving challenging engineering problems.
• Ability to thrive in a fast-paced research and development environment.
• Currently pursuing a Master's or Ph.D. degree in Electrical Engineering, Computer Engineering, Computer Science, Robotics, Machine Learning, or a related field.

In order to be considered for a summer internship with NXP you must be returning to school or graduating at the conclusion of the internship term. If you are graduating prior to July 2027 please apply to Entry Level full-time roles.

The base salary range for this position is as mentioned below per year. We also provide competitive benefits, incentive compensation, and/or equity for certain roles.
Company benefits include health. dental, and vision insurance. 401(k), and paid leave. Please note that the base salary range (OR hourly rate) is a guideline, and individual total compensation may vary based on a number of factors such as qualifications, skill level, work location, and other business and organizational needs. This base pay range is specific to California and is not applicable to other locations. A reasonable estimate of the base salary range as of the date of this posting is:

$64,400 to $107,500 annually

More information about NXP in the United States...

NXP is an Equal Opportunity/Affirmative Action Employer regardless of age, color, national origin, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, marital status, status as a disabled veteran and/or veteran of the Vietnam Era or any other characteristic protected by federal, state or local law. In addition, NXP will provide reasonable accommodations for otherwise qualified disabled individuals.

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