AI Researcher
3 weeks ago
We are the world's sports analytics leader, using cutting-edge AI technology to produce unique sports data and performance insights. These insights provide an edge to teams, leagues, media organizations, betting operators, and rights holders of all sizes. We use a variety of techniques to collect and analyze sports data, allowing our partners to discover contextual insights and derive value from them in brand new ways.
and data annotation services to collect any type of additional data you need; to design your game changing AI models for sport analytics applications.
Being part of our innovation team, you will also have the opportunity to publish original research in peer-reviewed journals and participate in conferences around the world, such as CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, and more.
You should be able to thrive in a dynamic environment that combines theoretical and applied research, systems building and collaborative work. Research and develop advanced AI technologies to improve our core ML/CV algorithms and to solve sport analysis problems in a practical and scalable way. Our research focus includes (but is not limited to) the following:
Computer vision (object detection, camera calibration, tracking, re-identification, motion capture, activity detection, activity prediction, etc.)
General deep learning topics including self-supervised learning, transfer learning, few-shot learning, active learning, generative models and graph neural networks, attention based models (transformers)
Collaborating with engineering team and product managers to produce quality AI software solutions as well as reviewing the team’s code and experiments to provide insightful feedback
Conducting original, publishable research, to be presented at conferences and contributing to the company’s IP portfolio
PhD degree in computer science, electrical/computer engineering, or a related quantitative field with research and development experience in computer vision and machine learning
Experience with full CV/ML life-cycle from model development, training, testing, deployment, monitoring, and refining and iterating
Solid programming skills in Python or C/C++ and familiarity with software development best practices
Strong publication record in computer vision, machine learning and deep learning in top tier conferences and journals
Ability to develop large-scale systems working with video/image data
Strong working knowledge of software architecture and data structure
Access to massive processing power, data, and whatever you may need to train large scale ML/CV models
Flexible work schedule
Freedom to publish the research work
Collaborative research with our world class academic network
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Grâce à nos ressources technologiques de pointe, comme l’intelligence artificielle, nous sommes en mesure de produire des données précises relatives au sport. Cela nous permet également de fournir des évaluations des performances. Nos techniques variées nous permettent de recueillir et d’analyser les données relatives aux sports. euse en intelligence artificielle, vous ferez partie d’une équipe exceptionnelle, talentueuse et innovante. En travaillant chez nous, vous aurez accès à de vastes bases de données; à de puissants outils –technologiques et infonuagiques - de traitement de données; à des services d’annotation de données capables d’amasser tous les types de données nécessaires. Tout cela vous permettra de concevoir des modèles d’intelligence artificielle révolutionnaires applicables à l’analyse de données sportives.
En vous joignant à notre équipe, vous aurez l’occasion de faire publier le résultat de vos recherches dans des revues spécialisées et mondialement reconnues dans le domaine de la recherche sur l’intelligence artificielle. Vous pourrez participer à des conférences partout dans le monde avec des organismes réputés comme : CVPR, ICCV, ECCV, NeurlPS, ICLR, ICML pour ne nommer que ceux-là.
Vous jouerez un rôle de premier plan dans l’avenir de l’analyse de données sportives, des paris, de l’entraînement sportif et des techniques de narration médiatique.
Travailler dans la recherche et le développement de technologies de pointe pour bonifier nos algorithmes d’apprentissage automatique et de vision par ordinateur Cela permettra de résoudre les problèmes d’analyse de données sportives de façon pratique et mesurable. La recherche sera centrée sur :
Plusieurs sujets reliés à l’apprentissage profond (l’apprentissage auto-supervisé, l’apprentissage par transfert, l’apprentissage avec peu de tentatives ou d’exemples, l’apprentissage actif, les modèles génératifs, les réseaux de neurones en graphes, la modélisation des mécanismes d’attention, ce que l’on appelle des transformers .
Collaborer avec l’équipe d’ingénieurs et avec les gestionnaires de production afin de créer des logiciels d’intelligence artificielle de qualité supérieure;
Mener des recherches novatrices dont les résultats pourraient être publiés ou présentés lors de conférences et ajoutés au répertoire de propriétés intellectuelles tenu par Sportlogiq.
D’un doctorat en informatique, en génie informatique, en génie électrique, en recherche quantitative ou tout domaine connexe ET de l’expérience en recherche et développement dans le domaine de l’apprentissage automatique et de la vision par ordinateur;
De l’expérience sur toutes les étapes de la conception d’outils dans le domaine de l’apprentissage automatique et de la vision par ordinateur:
À partir de l’élaboration du modèle initial, en passant par la formation, les expérimentations, le déploiement, la supervision, la finition et jusqu’à la réitération du processus;
De l’expérience avec les systèmes d’apprentissage profond (par exemple : Pytorch ou Tensorflow );
D’excellentes habiletés en programmation en C/C++ et la connaissance des pratiques exemplaires en développement de logiciels;
D’avoir fait publier plusieurs articles sur la vision par ordinateur, sur l’apprentissage automatique et sur l’apprentissage profond. De la capacité d’élaborer des systèmes de grande envergure, des systèmes qui travailleront à partir de données visuelles;
D’une grande connaissance de la structure des logiciels et de la structure des données;
D’une excellente capacité à vous exprimer en français et en anglais.
De nombreux avantages sociaux;
La possibilité de mener des recherches novatrices dont les résultats pourraient être publiés ou présentés lors de conférences;
L’accès à de vastes bases de données; à de puissants outils –technologiques et infonuagiques - de traitement de données et tout ce dont vous pourriez avoir besoin pour faire de la modélisation de grande envergure en apprentissage automatique et en vision par ordinateur.
La possibilité de faire de la recherche en collaboration avec notre réseau universitaire de haut niveau.
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