Working Student AI for Radar Perception
📌Hamburg, Germany 🇩🇪
⏱︎ internship
🧙♂️ entry-level
hybrid
At NXP Semiconductors , our Radar Architecture team develops advanced AI-driven radar solutions to enable intelligent perception for next-generation automotive applications. We work across the stack—from low-level radar signal understanding to multi-sensor (camera + radar) scene perception—always with a strong link to embedded deployment and real-world use cases. Our work supports production-level systems in partnership with major Tier-1s like CARIAD , Aptiv , and Continental .
Key Responsibilities
- Assist in developing and evaluating computer vision models for scene understanding using radar and camera inputs
- Develop data pre-processing algorithms for training and validation
- Support the implementation of radar-camera fusion pipelines using PyTorch
- Run model experiments on embedded platforms and analyze performance metrics
- Help visualize outputs in Bird’s Eye View (BEV), image, or 3D voxel spaces
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Collaborate with cross-functional teams and contribute to technical discussions
- Currently pursuing a Master’s degree in Computer Science, Electrical Engineering, Robotics, or a related field
- Experience with PyTorch or TensorFlow for training deep learning models
- Familiarity with basic radar signal processing or computer vision
- Interest in embedded AI and multi-modal perception
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Strong Python skills and motivation to contribute to real-world ML systems
- Familiarity with deployment tools such as TensorRT, TVM, or OpenCL
- Experience with large-scale datasets like nuScenes, Waymo Open Dataset, or K-Radar
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Exposure to 3D vision or volumetric methods for scene understanding
- Contribute to industry-relevant projects in radar perception and fusion
- Gain hands-on experience with embedded AI in a production context
- Work alongside experts in signal processing, hardware, and machine learning
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Flexible hours and hybrid work setup to support your academic schedule
Senior Embedded Software Engineer
@ Embedd 
What we're looking for
At embedd.it, we power hardware-software integration in embedded devices. We turn fragmented semiconductor chip data into configurable digital twins, then deterministically generate code, tests, and documentation – making integration faster, cheaper, and resilient to supply chain shocks.
We’re looking for a true legend – someone with abstract thinking and deep expertise in low-level software development. You’ll build vendor-agnostic tooling for MCU and peripheral integration to solve hardware-software integration once and for all. We work at the intersection of embedded systems, code generation, compilers, and machine learning. It’s your chance to help redefine how low-level development is done.
Responsibilities
- Drive the architecture of the driver structures and system layout
- Define scalable patterns for cross-architectural integration across bare-metal, Zephyr, Linux, and other environments
- Deconstruct complex SoC device trees and translate hardware descriptions into structured internal models for automated reasoning
- Partner with the ML team to shape data and annotation models for AI-driven data-extraction tooling
Qualifications
- 5+ years of experience in embedded systems development, including bare-metal and RTOS-based systems
- Proficiency in C/C++
- Familiarity with firmware configuration, SoC bring-up, and system-level debugging
- Hands-on experience with code generation tools, or low-level compiler/decompiler/emulator technologies
- Strong background in embedded toolchains: compilers, linkers, debuggers, and build systems
- Python or scripting for automation and tooling is a plus
- Experience with functional-safety standards is a plus
Why embedd.it?
- Dynamic, venture-backed team of engineers challenging the status quo 🚀
- Work at the intersection of embedded systems, code generators, compilers, and ML 🤖
- Unusual challenges requiring out-of-the-box abstract thinking 🧠
- Competitive compensation: cash + equity 💰
- Remote work possible 🌍
About Us
embedd.it is a UK-based startup reinventing embedded development. Our platform transforms unstructured semiconductor data into structured digital twins, enabling automatic generation of drivers, tests, and documentation. We're building a single, traceable source of truth to make integration fast, vendor-agnostic, and future-proof.
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Employment
⏱︎ internship
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Experience
🧙♂️ entry-level
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Working model
hybrid
-
Skills
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Industry
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