Junior Applied Deep-Learning (m/f/d) | Signatrix
Signatrix uses state-of-the-art deep learning and artificial intelligence technology to bring transparency and intelligence to brick and mortar retail. Thanks to our solutions, the security cameras of our clients can independently track, measure and evaluate customer behavior and patterns as well as theft incidents and conversion rates in real time.
Europe's biggest retail chains already enhance the processes and customer experience in their stores with the help of our solutions. Now that we have also secured funds by experienced investors, who will support us on a strategic and operational level, we are looking for a Junior Applied Deep-Learning (m/f/d) to join our team.
- Development of video based action understanding models
- Implement deep learning models for person detection, pose estimation, item classification, and action recognition
- Human behavior analytics
- Experiment with model architectures, transfer learning strategies, data augmentation approaches, data sampling strategies, hyperparameter search
- Implementation of highly hardware efficient sota deep learning models and development of original deep learning models
Don't worry if you don't tick all of the below!
- At least 1 year of industry experience
- B.Sc./M.Sc. (strong math background preferred) or equivalent industry experience
- Understanding of convolutional neural networks and the tradeoffs of different architectures, loss functions, and regularizers
- Python, Tensorflow / PyTorch, Docker
- Experience with professional software development processes and working with linux based systems
- You have implemented at least one research paper in code (show us on Github)
- Experience with video based deep learning systems, computer vision pipelines and a focus on efficient computation are preferred
- Active open source contributions and/or development community involvement would be great as well as participation in original research
What we offer:
- Competitive salary
- Possibility to earn shares in the company via ESOP
- Lunch on the company
- Public transport subsidy