Neural networks are both computationally intensive and memory intensive, making them difficult to deploy on limited hardware resources and slowing down the inference time. To address this limitation, many techniques exist such as quantization and pruning. Developing models that are light and fast is a pre-requisite when deploying in real-life conditions, when speed is an important factor to make the authentication process as smooth and transparent for the end user as possible, and when large enough infrastructures may not be available.

Another challenge when running models in real life conditions is that models need to perform not only well but well on everyone, irrespective of their gender, origin, age, socio-economic situation etc. Conscious or unconscious bias is often cited as a shortcoming of facial verification systems. At Unissey, we are thriving for a universal use of technology and we are hence committed to provide algorithms that are actively fighting bias.

The internship objectives are hence twofold:

• Optimizing current algorithms, by applying compression techniques to limit the size and inference time of Unissey’s models;
• Developing techniques that mitigate bias to help Unissey building a fairer AI that works equally well for everyone.

For both research topics, the intern will be asked to carry extensive research about the state-of-the-art techniques on the topic and to develop innovative solution using the existing literature and the intern’s knowledge of machine learning.

• Pursuing an MSc / MEng degree in computer science, applied mathematics or any related technical field.
• Prior experience in building and training deep learning algorithms.
• Good theoretical knowledge in computer vision, neural networks, and other DL techniques.
• Excellent coding skills in python (experience with pytorch is a plus).
• Great sense of initiative, autonomy and scientific rigour.
• Curiosity and a strong interest for DL/ML topics and the latest scientific breakthrough.
• Proficiency in English (ability to quickly read and understand research papers).
• Prior experience with Git and collaborative tools is a plus.
• Personal side projects or Kaggle competitions are a plus

Details :

• Duration : 6 months.
• Salary : according to profile and past experiences.
• Location : 4 rue du Caire, 75002 Paris.
• Start date : March 2022.

Quick screening call.

Technical test, to be completed at home.

Final interview, including a technical part, and a meeting with different members of the R&D team to evaluate your motivation / cultural fit.