Machine Learning Internship - Munich

The vacancy is within Business Line Radio Frequency Processing (RFP) which is one of the core businesses of NXP. NXP has been a leader in RF innovation and technology for more than 60 years, offering an extensive portfolio of RF solutions. As the market leader in Automotive Radar we are continuously innovating to enable our Tier1 and OEM customers shape the car architecture of the future and make driving more secure.

Job Summary:

• You will be part of the Advanced Radar Solutions Team in Munich building next-gen automotive radar and self-driving perception technologies using advanced machine learning techniques.
• Develop prototype solutions using AI models and interface with other engineering teams and gain exposure to the entire software development lifecycle (including annotated data collection/simulation, database management and data analysis)
• Opportunities to apply your machine learning knowledge to solve cutting-edge automotive radar challenges such as object detection, instance segmentation as well as model optimization.
• Opportunities to apply your hands-on software engineering and development skills using various tools like custom IDEs, compilers and SDK for edge SoCs
• Term: 6 month

Job Qualifications:

• Hands-on skills
  • Python and ML frameworks like PyTorch and Tensorflow including visualization tools like Tensorboard
  • Ubuntu or any Debian OS
  • C/C++
  • Robot Operating System (ROS)
• Knowledge base
  • Machine learning/neural network principles and programing models,
  • Experience with state of the art network architectures (CNN, LSTM, MLPs)
  • Experience with basic FMCW radar signal processing techniques is a bonus.
• Strong communications, documentation, and presentation skills
• Highly self-motivated and enjoying solving difficult challenges
• Currently enrolled in or entering a Master's or PhD degree program in Electrical Engineering, Computer Science, or related fields.

In order to be considered for an internship with NXP, you must be returning to school (or graduating) at the conclusion of the internship term. If you are graduating prior to September 2022, please apply for positions labeled “Graduate Hire” or “Entry Level”.