Intern (f/m/d) Agentic AI for Signal Processing in Embedded Systems
NXP Semiconductors Software & IT
InternshipHybridMunich, Germany
About the role
Support the exploration and prototyping of Agentic AI techniques for proprietary DSP and ASIC architectures.
Contribute to researching compiler technologies, analyzing ISA documentation, developing proof-of-concept AI agents, and evaluating code generation and optimization workflows for embedded compute platforms. You will work closely with experienced engineers and gain hands-on experience in applying AI-driven approaches to real-world semiconductor development challenges.
Responsibilities
Investigate state-of-the-art agentic AI and compiler technologies.
Develop prototypes for documentation-assisted code generation and optimization.
Work with MLIR, LLVM, ONNX, and embedded toolchains.
Automate analysis, validation, and performance evaluation workflows.
Document findings and present results to engineering teams.
Requirements
Studies in Computer Science, Electrical Engineering, or related field.
Basic knowledge of Python and C++.
Interest in AI, compilers, embedded systems, or machine learning.
Strong analytical and problem-solving skills.
Nice to have
Experience with LLVM/MLIR, ONNX, MATLAB, or embedded DSP development.
Familiarity with machine learning model deployment and performance optimization.
What We Offer:
An attractive monthly salary
Flexible working hours
The possibility to work in a hybrid setup
Access to an on-site cafeteria
Networking initiatives and Employee Resource Groups such as Young Community, No Extra Planet, NXP Equal, Women in NXP, and more — fostering both professional and personal exchange
Please note: The successful candidate may/will be responsible for security related tasks. The assignment may/will be in scope of security certifications, therefore a conscious and reliable way of working is necessary.
More information about NXP in Germany...
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— Published by NXP Semiconductors. Apply on the employer's own posting.
Skills
performance optimization
signal processing
machine learning
embedded systems
documentation
optimization
validation
python
matlab
c++
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