Working Student Computer Vision and Deep Learning

vor 5 Monaten


Berlin, Deutschland Signatrix GmbH Vollzeit

**Your mission**:
We are looking for a highly motivated working student/Intern to join us.
As part of your work:

- you will support the team in developing and optimizing camera-based computer vision algorithms within the retail environment
- you will support the engineering team, in all steps of the data preparation pipeline (annotation, data export, data control etc.)
- you will contribute to the test automation framework
- you will report bugs and follow up on their resolution
- you will prepare reports and literature surveys for related topics

**Your profile**:
You have started to specialize in and are eager to learn more about Deep Learning and Computer Vision
and you are a student in Computer Science, Mathematics, Robotics or a comparable major, enrolled in a German university
- Clean and structured coding skills (Python required, C++ is a plus)
- Knowledge of common deep learning frameworks (Pytorch, Tensorflow)
- Knowledge in the fields of object classification, detection and tracking
- [Nice to have] Loss function design, quantization, model compression, knowledge distillation
- [Nice to have] CNN/DNN hardware acceleration
- Familiar with the following tech stack:

- Git workflow, Docker
- [Nice to have] Openvino, TensorRt, CUDA
- Proficiency in English; German is a plus
- In which semester are you?
- In which city are you located in?
- How often can you come to the office?

**Why us?**:

- ** A highly driven, smart and international team**:

- ** An attractive remuneration**:

- ** Lunch at company expense**:

- ** Flexible working hours and choice of work location**:

- ** Diverse development opportunities**:
**About us**:
We are Signatrix, and together we are Remaking Retail. Our goal is to improve existing infrastructures and make them "smart" in a matter of weeks. Connecting with store security cameras, we use Artificial Intelligence to analyse whatever is happening in a store — automatically and in real-time.



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