Embedded Machine Learning & Radar Processing Intern - Summer 2027
Core
Develop next-generation automotive radar and perception systems for advanced driver assistance and self-driving vehicles using edge AI.
Role type
Embedded Machine Learning & Radar Processing Intern
Builds
Full radar system proof-of-concept (PoC) from ML models to embedded deployment
Domain
Automotive, Embedded Systems, Machine Learning
Deliverable
production ML models
Required skills
Machine learning and deep learning development, Python, PyTorch, TensorFlow, C, C++, Embedded C, Embedded Linux, Hardware-in-the-Loop (HIL) testing, Robot Operating System (ROS/ROS2)
Preferred skills
Model quantization, acceleration, or performance optimization for edge devices, NXP eIQ Auto, FPGA-based emulation platforms, AI accelerators, NPUs, DSPs, heterogeneous computing architectures
Technologies
GCC, GDB, NXP eIQ Auto, ROS/ROS2
Responsibilities
Benchmark and optimize AI/ML models on NXP hardware platforms, Build and enhance the software stack required to deliver a full radar system proof-of-concept (PoC), Collaborate with multidisciplinary teams spanning AI, signal processing, embedded systems, and semiconductor hardware
Seniority
Intern
