Senior Scientist – Computer Vision - Remote

Overview

Our client is an applied research organization in artificial intelligence, recognized for its strategic role in the development and transfer of innovative solutions. It supports organizations in reducing technological uncertainties and accelerating the time-to-market of their products, through tailor-made applied research projects.

In Short

• Simultaneous participation in the implementation and supervision of several computer vision projects addressing industrial issues.
• Proposal and implementation of vision research projects on topics of scientific and business development interest.
• Participation in the evaluation of new projects (technical complexity, challenges, feasibility, etc.).
• Contribute to the drafting of service offers.
• Contribute to the scientific and technical outreach of the research organization by organizing activities or disseminating relevant advances to the community through various means.
• Keep knowledge up to date, contribute to internal and external scientific seminars to share know-how.
• Ensure and document in-depth scientific watch activities on advances in computer vision, and share this knowledge within the research organization.

Requirements

• PhD in computer science with specialization in computer vision.
• Minimum five years' experience in vision and deep learning.
• Excellent writing skills in various contexts (scientific journal, technical documentation, popularization, etc.).
• Demonstrable experience in vision (classification, semantic segmentation, object detection); experience with generative models and more particularly multimodal models.
• Ability to understand the needs of users/domain experts and extract technical requirements, develop a work plan and lead a team in the realization of solutions.
• Proficiency in Python and a deep learning library (Pytorch, Tensorflow).
• Fluency in spoken and written French and English.

Benefits

• Experience in image processing and remote sensing/geospatial.
• Experience in carrying out large-scale projects.
• Knowledge of MLOps.
• Knowledge of using high-performance computing clusters.
• Extensive knowledge of statistics, probability or other areas of mathematics relevant to machine learning in general.
• History of scientific publications.
• Contributions to open-source projects.