Radar ML & Edge AI Intern — Autonomous Driving

OpenTalent; San Jose (CA); On-site; USD 34,000 - 48,000; Part time

Job summary

NXP's Innovation R&D team in Silicon Valley invites interns to 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 powering advanced driver assistance and self‑driving vehicles.

You will contribute to ML/AI development, embedded software, and edge deployment on real hardware, using Python, C/C++, and ROS/ROS2.

Qualifications

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

Responsibilities

• Contribute to automotive radar and perception solutions for vehicle intelligence.
• Apply software engineering skills using IDEs, compilers, SDKs, and toolchains for edge AI SoCs.
• Benchmark and optimize AI/ML models on NXP hardware platforms.
• Build software stack for radar PoC from ML models to embedded deployment.
• Collaborate with AI, signal processing, embedded systems, and hardware teams.

Skills

Python

PyTorch

TensorFlow

Model optimization

C++

Embedded C

ROS/ROS2

GCC

GDB

Embedded Linux

Education

Master’s or Ph.D. in Electrical Engineering, Computer Engineering, Computer Science, Robotics, or related field

Tools

GCC

GDB

ROS/ROS2

Embedded Linux

Job description

NXP's Innovation R&D team in Silicon Valley invites interns to 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 powering advanced driver assistance and self‑driving vehicles.

You will contribute to ML/AI development, embedded software, and edge deployment on real hardware, using Python, C/C++, and ROS/ROS2.