Computer Vision Scientist
SkillCorner · Paris
Join SkillCorner's 16-person Computer Vision team in Paris, building deep learning models for player detection, tracking, re-identification and recognition from broadcast footage. You will own models end to end, from training and evaluation pipelines through to deployment in an AWS production pipeline used by professional sports organisations.
The application is with the employer, never with us. Posted 2 weeks ago. Last checked today.
The advert, from SkillCorner
About SkillCorner
At SkillCorner, we turn a single broadcast camera feed into rich sports data, 100% automatically. Our Computer Vision and Machine Learning algorithms detect every player, the ball and the referees, locate them on the field, track them frame by frame and recognize who is who.
Since 2016, we have grown into a global leader in our field. We cover more than 150 men’s and women’s competitions, hold over 100 billion data points on more than 100,000 professional players, and are trusted by more than 350 football, basketball and American football teams. Clubs, federations and agencies use our data to rethink how they analyze performance, scout and recruit.
We are a team of about 150 people around the world, with our tech team based mostly in Paris. The Computer Vision team, 16 people strong, sits at the heart of our mission: it uses state-of-the-art deep learning to deliver precise, high-quality tracking data, at scale and in production.
The role
We are looking for a Computer Vision Scientist to join our Computer Vision team. You will bring solid experience in deep learning applied to computer vision to the models that power our tracking data, from detection and tracking to re-identification and recognition.
You will own key models: designing and training architectures, building training and evaluation pipelines, and pushing performance to production-grade quality. You will work with tools like PyTorch/TensorFlow, OpenCV and deep learning architectures (CNNs, Transformers, etc.). You will make technical decisions with real downstream impact and help raise the research and engineering standards of the team.
This role sits where applied research meets production. Your work will go from experiment to live deployment, used by professional sports teams and organizations around the world.
What you’ll do
Design, train and optimize deep learning models for detection, tracking, re-identification and recognition
Own key components of our tracking pipeline, from data and training to evaluation and deployment
Make and defend technical decisions, grounded in a solid understanding of the theory behind the models you build
Monitor the state of the art, analyze model performance and turn new ideas into concrete improvements
Establish the metrics and tooling that measure tracking quality, and drive continuous improvement from one release to the next
Bring research algorithms into our AWS production pipeline and keep performance stable when new models go live
Raise the bar on engineering and research practices: code reviews, testing, reproducible experiments and documentation
Work with Product, Engineering and Operations to turn client needs into concrete tracking improvements
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