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Salary
≈ $61k – $119k per year (Estimated)
Location
Hybrid (Paris, France)
Seniority
Senior · 4+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 29, 2026. First seen by Alion on Oct 22, 2026.

Overview
Company
Impact
Profile match
SkillCorner extracts player and ball tracking data from ordinary broadcast football footage using computer vision. Clubs, leagues and media use the resulting physical and tactical metrics without installing cameras in stadiums. The company is headquartered in Paris and covers competitions worldwide.

Join SkillCorner, a global leader in sports data analytics. As a Senior Computer Vision Scientist, you will work on cutting-edge deep learning models for basketball tracking. You will design architectures, build training and evaluation pipelines, and push performance to production-grade quality. Your work will have a real impact on professional basketball teams worldwide.

Missions

  • Conception, formation et optimisation de modèles d'apprentissage profond pour la détection, le suivi, la ré-identification, la reconnaissance et l'estimation de pose.
  • Responsabilité des composants clés du pipeline de suivi du basketball de bout en bout, de la collecte de données et de la formation à l'évaluation et au déploiement.
  • Intégration d'algorithmes de recherche dans notre pipeline de production AWS et maintien de la performance stable lors de la mise en ligne de nouveaux modèles.

Profil recherché

* 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

### Why join us

* Real impact: your work ships to production and is used by more than 350 professional teams worldwide

* Hard, exciting problems: state-of-the-art computer vision on real broadcast video, at scale

* Ownership: own key models end to end and shape how our tracking technology evolves

* A great team: passionate people at the crossroads of AI and sport, with a tech team in the heart of Paris

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