Embedded AI Engineer Intern [IDA: 00051]

Since its spin-off in September 2025 AUMOVIO continues the business of the former Continental group sector Automotive as an independent company. The technology and electronics company offers a wide-ranging portfolio that makes mobility safe, exciting, connected, and autonomous. This includes sensor solutions, displays, braking and comfort systems as well as comprehensive expertise in software, architecture platforms, and assistance systems for software-defined vehicles. In the fiscal year 2024 the business areas, which now belong to AUMOVIO, generated sales of 19.6 billion Euro. The company is headquartered in Frankfurt, Germany and has about 87.000 employees in more than 100 locations worldwide.

As a team member of the Innovation team, you will be involved in the software development of innovative system solutions. This role offers hands-on experience in developing algorithms and systems that enable intelligent visual understanding for real-world applications, along with opportunities to contribute to research and innovation.

Intern would be working together with the R&D innovation team in the following tasks:

a) Assist in designing, implementing, and optimizing computer vision and perception algorithms.

b) Develop and test object detection, tracking, and recognition models using state-of-the-art techniques.

c) Conduct research on emerging computer vision methods, including literature reviews and benchmarking new algorithms.

d) Experiment novel approaches for object detection and perception.

e) Work with large datasets to train and evaluate models.

f) Collaborate with senior engineers and researchers to integrate vision algorithms into production systems.

a) Familiar with programming languages such as Python, C/C++, and embedded software development concepts.

b) Understanding of embedded systems, including microcontrollers, embedded Linux, hardware-software integration, and real-time systems.

c) Understanding of AI/ML fundamentals, including deep neural networks, model training, inference, and performance evaluation.

d) Exposure to computer vision and perception systems, including image processing, object detection, and feature extraction techniques.

e) Familiarity with deep learning frameworks such as PyTorch or TensorFlow, and experience with model deployment pipelines is an advantage.

f) Understanding of Edge AI concepts, including model optimization, quantization, pruning, and deployment on resource-constrained devices.

g) Exposure to AI acceleration technologies such as CUDA, TensorRT, OpenVINO, ONNX Runtime, or NPU-based platforms will be an advantage.

h) Familiarity with embedded AI hardware platforms such as NVIDIA Jetson, Raspberry Pi, STM32, ESP32, Qualcomm RB platforms, or similar edge computing devices is an advantage.

Ready to take your career to the next level? The future of mobility isn’t just anyone’s job. Make it yours! Join AUMOVIO. Own What’s Next.