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Artificial Intelligence
AI Research Intern

AI Research Intern

Job target 

You will join the AI Research team as an intern to test new techniques in Deep Learning and contribute to adapt them to our use-cases, mostly linked to object detection and image segmentation. You will be part of a dedicated team that constantly watches the latest scientific papers and technological posts and implements the best solutions to improve our processes and our products.
It means that you will learn from experts in the dedicated AI team and work on state-of-the-art topics in the field of deep learning. You will also collaborate closely with our AI framework team to transform innovative and smart ideas into tools usable by everyone in the AI team. You will have the opportunity to work with both our internal business experts to understand the needs of our clients, and our data management team to access our vast database of labeled satellite images and expand it, if needed.

Main areas of accountability

Contribute to and follow a rigorous experimental protocol to tackle a scientific problem

Main activities

- Contribute to the monitoring of the latest advances in machine learning, especially deep learning for computer vision
- Participate in the design of experimental protocols to test cutting-edge techniques in innovative domains, such as few-shot learning, continuous and active learning, hierarchical learning or model ensembling
- Help in implementing and refining methods from scientific articles, git repositories or other publications to make them usable for our use-cases, and possibly work closely with the AI framework team to integrate them into production
- Suggest new ideas to push beyond state-of-the-art solutions
- Contributing to the specifications of our AI framework to improve the productivity of the whole AI team
- Work closely with the GIS team and business experts to understand the data available and use it in the best possible ways

Influence on results

- Education in the field of machine learning, computer science, statistics and/or mathematics
- At least one practical experience in computer vision / deep learning (can include internships, online courses or personal side projects)
- Knowledge on DL techniques, especially CNN architectures for Semantic Segmentation and Object Detection
- Good skills in Python
- Experience of building and training DL models in a framework such as Keras/TensorFlow or PyTorch
- Comfortable in a UNIX/Linux environment
- Good communication and team work skills
- Rigorous, creative and meticulous mind
- Willingness to take on challenges, show resiliency and like to always learn new skills

- Knowledge of some classical Computer Vision techniques
- Proficiency with Docker, Github
- Experience in technological watch and scientific papers reading
- Experience working with remote sensing images
- Experience working in a startup environment
- Experience working in a laboratory or research environment