Who are we
With Reminiz, viewers can instantly access the track record of any on-screen politician, singer, actor or sportsman thanks to a proprietary face recognition technology. Reminiz is able to identifiy any public figure on TV in order to provide users with additional information and related content in single tap.
While watching TV, users can buy the book of this interviewed writer, watch the latest movie of this actor, check this football player score or learn more about a debating politician at no efforts.
Reminiz works side by side with movie studios, TV channels and TV providers to revolutionize the way people watch TV and the way we create movies with data.
Reminiz uses computer vision algorithms to analyze video libraries or live TV streams.
Today, our efforts are focused on:
- Improving the algorithms' accuracy
- Accelerating the recognition pipeline
- Securing the product to comply with clients' video security policies
- Scaling up the infrastructure worldwide
As part of the team, you will work on the aggregation of annotated data into a large and unified TV video dataset. Together with your fellas, you will also manage the reliability of the data and implementation of test pipelines. Finally you will also be free to dig further and test new methods in order to improve products' performances.
Challenging the industry
Joining the Reminiz R&D squadron means working on a scalable product based on machine learning algorithms. It also means being part of a team made of passionate people who want to keep learning about everything related to computer sciences (scripting, unix systems, web development, deep learning, ...). Our work has already been rewarded by tech giants such as Microsoft, Nvidia, Orange. Reminiz is growing fast and quickly expanding overseas. This is not an overnight success but the result of a talented and hard-working team.
So, if you want to be challenged while challenging the industry, join us on this journey.
Metro: Sentier / Grand Boulevard
Python Unix Computer vision Machine learning
Exp. in Web dev Exp. in Deep learning Exp. with SCRUM method
Object: CVML Internship
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