> Markdown version of [/jobs/ext/4007066-senior-computer-vision-scientist-basketball-tracking](https://www.wearedevelopers.com/jobs/ext/4007066-senior-computer-vision-scientist-basketball-tracking). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Computer Vision Scientist - Basketball Tracking - **Company:** SkillCorner - **Location:** Paris, France - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Architectural Patterns, Computer Vision, Batch Processing, Software Code Optimization, Software Quality, Code Review, Software Debugging, Python (Programming Language), Object Detection, OpenCV, Tensorflow, Graph Neural Networks, Pytorch, Evaluation Pipelines, Large Language Models, Deep Learning, Information Technology, Machine Learning Operations, Docker - **Published:** October 29, 2026 - **Apply:** https://www.welcometothejungle.com/en/companies/skillcorner/jobs/senior-computer-vision-scientist-basketball-tracking_paris ## About the Role * A graduate degree or PhD in engineering, computer science, mathematics or a related field * 4+ years of hands-on experience in computer vision with deep learning, including production systems * Strong deep learning expertise in areas such as people tracking, re-identification, people, face and object recognition, camera calibration, body pose estimation and action recognition * Proven experience designing, training and shipping detection, tracking or recognition models to production, not only research prototypes * Experience with data-centric work: dataset curation, annotation strategies and handling noisy labels * A strong grasp of the theory behind modern architectures (CNNs, Transformers, GNNs), and the judgment to choose between approaches * Experience assembling several algorithms into one reliable system * The ability to drive technical decisions independently and explain trade-offs * Strong Python for ML: clean, tested, deployable code, with PyTorch or TensorFlow and OpenCV * Hands-on experience with AWS workflows and Docker * Excellent communication skills in English Nice to have * French: a strong plus, as the team is French-speaking * Experience with multi-object tracking and re-identification in crowded scenes, or with sports or broadcast video * Experience with camera calibration, homography estimation or 3D geometry * Experience running ML pipelines at scale in the cloud (GPU inference, batch processing) * Notions of MLOps and model optimization * Experience using LLM-based agents to speed up development, debugging or support * Publications at top computer vision or ML venues (CVPR, ICCV, ECCV, NeurIPS) * Knowledge of, or a genuine interest in, basketball ## Description We are looking for a Senior Computer Vision Scientist to join our Basketball Tracking team, reporting to the Team Lead. You will bring deep expertise in deep learning to the models that power our basketball tracking data, from detection and tracking to re-identification, recognition and pose estimation. You will own key models end to end: designing architectures, building training and evaluation pipelines, and pushing performance to production-grade quality. You will make architectural 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 the professional basketball teams SkillCorner works closely with around the world., * Design, train and optimize state-of-the-art deep learning models (CNNs, Transformers, GNNs) for detection, tracking, re-identification, recognition and pose estimation * Own key components of the basketball tracking pipeline end to end, from data and training to evaluation and deployment * Make and defend architectural 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 Engineering excellence * Bring research algorithms into our AWS production pipeline and keep performance stable when new models go live * Optimize models for accuracy, speed and cost at scale * Raise the bar on engineering and research practices: code reviews, testing, reproducible experiments, documentation and smart use of LLM-based tools * Investigate issues in the pipeline and keep code quality high * Understand client needs and product stakes, and translate them into concrete tracking improvements * Share your knowledge and support more junior team members as they grow