SkillCorner

www.skillcorner.com

4 Jobs

107 Employees

About the Company

SkillCorner collects sports data 100% automatically from a single camera feed. The company, now a global leader in its field of expertise, develops Computer Vision and Machine Learning algorithms that can detect all the moving objects (each players, the ball and the referee) in the image, locate them on the pitch, track them frame by frame, and recognize them. From this raw tracking data, SkillCorner produces Performance indicators, Game Intelligence metrics, and Visualizations that are used by clubs, national federations, and player agencies. In football, SkillCorner covers more than 150 competitions (both Women's and Men's), holds over 100 billion data points on more than 100 000 professional players. More than 200 football clubs worldwide use its data daily for recruitment, game and opponent analysis. The first sport covered by SkillCorner was football, but the company has recently expanded into American football and basketball and has already signed its first clients in the NFL and NBA. #SportsData #SportsAnalytics

Listed Jobs

Company Name: SkillCorner
Job Title: Junior Computer Vision Scientist
Job Description: **Job Title:** Junior Computer Vision Scientist **Role Summary:** Design, implement, and optimize deep‑learning based computer vision algorithms for extracting player and ball positions from broadcast sports video. Collaborate with senior researchers to transition prototypes into production‑ready solutions that deliver high‑precision tracking data for sports analytics. **Expectations:** - Demonstrated hands‑on experience with deep learning for computer vision (internship, project, or similar). - Strong analytical curiosity, rigor, and willingness to learn. - Effective communication in English and French. - Ability to work collaboratively in a fast‑paced, interdisciplinary team. **Key Responsibilities:** - Develop and fine‑tune player/ball detection, tracking, and team‑clustering models. - Implement camera‑calibration pipelines to map 2D detections to 3D field coordinates. - Optimize model latency through quantization, pruning, or other techniques. - Conduct data preprocessing, annotation, and visualization for model training and evaluation. - Write clean, maintainable Python code and integrate models into the production stack. - Participate in code reviews, technical discussions, and cross‑functional meetings. **Required Skills:** - Proficiency in Python and deep‑learning frameworks (e.g., PyTorch, TensorFlow). - Practical experience with computer‑vision libraries (OpenCV, torchvision, etc.). - Familiarity with model optimization (quantization, pruning, inference acceleration). - Experience handling large image/video datasets and visualizing results. - Strong problem‑solving abilities and attention to detail. - Excellent written and verbal communication in English; functional French. **Required Education & Certifications:** - Bachelor’s or Master’s degree (or PhD) in Computer Science, Engineering, Mathematics, or a closely related field. - No specific certifications required; demonstrable project or internship experience is essential.

Company Name: SkillCorner
Job Title: Computer Vision Team Lead – American Football
Job Description: **Job Title** Computer Vision Team Lead – American Football **Role Summary** Lead the development and delivery of a computer‑vision‑based tracking pipeline for American football broadcast footage. Manage a multidisciplinary team of engineers and researchers, define technical strategy, ensure high‑quality data extraction, and align solutions with product and customer needs. **Expectations** - Deliver robust, accurate tracking of players and ball in real‑time broadcast scenarios. - Scale CV pipelines for production deployment across varied competitive levels. - Maintain continuous improvement through research and adoption of state‑of‑the‐art methods. **Key Responsibilities** - Lead, mentor, and grow a team of computer‑vision engineers and researchers. - Architect and oversee multi‑object tracking, player detection, ball tracking, camera calibration, pose estimation, and related modules. - Collaborate with data‑pipeline, annotation, MLOps, and product teams to integrate solutions. - Define and maintain technical roadmaps in partnership with product and engineering leadership. - Ensure quality, scalability, and robustness of models across diverse broadcast conditions. - Stay current on academic and industry trends; drive adoption of innovative techniques. **Required Skills** - 5+ years in computer vision or machine learning, with 1–2+ years in technical leadership. - Deep expertise in video‑based object detection, tracking, and scene understanding. - Proficiency with PyTorch or TensorFlow. - Strong organizational, communication, and stakeholder‑management skills. - Fluency in English; proficiency in French required. - Experience scaling CV pipelines into production environments (preferred). - Knowledge of American football rules, gameplay structure, and broadcast formats (bonus). **Required Education & Certifications** - Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or related discipline. ---

Company Name: SkillCorner
Job Title: Machine Learning Engineer
Job Description: **Job Title:** Machine Learning Engineer **Role Summary:** Contribute to the end‑to‑end ML pipeline by building scalable deployment tools, managing the full ML lifecycle, optimizing models for compute and cost, and guiding data scientists through best practices in a fast‑paced tech startup. **Expactations:** Collaborate closely with Software and Data Science teams; accelerate model delivery to production; maintain high performance and low latency model inference; continuously improve tooling and processes; foster a culture of robust ML engineering. **Key Responsibilities:** - Design and implement production‑grade training and testing tooling for data scientists. - Own the ML project lifecycle: data ingestion, model training, code versioning, deployment, and monitoring. - Optimize neural networks and algorithms for reduced compute time and cloud spend (e.g., model compression, TensorRT inference). - Mentor data scientists on ML best practices, reproducibility, and efficient code. - Acquire and apply video engineering skills relevant to media-centric products. - Integrate CI/CD pipelines, container orchestration, and observability solutions to streamline releases. **Required Skills:** - Strong Python programming and deep knowledge of ML theory and practice. - Proficiency with TensorFlow, ONNX, PyTorch, TensorRT, CUDA, and related libraries. - Experience with Docker, Amazon EKS, and orchestrators (e.g., Step Functions). - Working knowledge of AWS services (EC2, EKS, RDS, Lambda) and other cloud platforms (GCP, Azure). - Comfortable with Linux environments, Git, and collaborative development workflows. - High motivation, adaptability, and a start‑up mindset. **Required Education & Certifications:** - Relevant university degree or equivalent professional experience in computer science, data science, or software engineering (preferred).

Paris, France

Hybrid

05-11-2025

Company Name: SkillCorner
Job Title: Stage en Computer Vision
Job Description: Job title: Computer Vision Intern Role Summary: Design and implement computer‑vision and machine‑learning solutions to collect, interpret, and analyze data from football and basketball match broadcasts, enabling player and ball tracking and other analytics. Expectations: Work autonomously on a project covering data acquisition, solution design, training, validation, and production deployment. Bring exploratory thinking and propose innovative solutions. Key Responsibilities - Acquire and preprocess video data from sports broadcasts. - Build object‑detection pipelines for players, ball, and other relevant entities. - Perform image segmentation for field lines, etc. - Execute camera calibration and tracking algorithms to generate player/ball trajectories. - Design, train, and validate deep‑learning models using TensorFlow or PyTorch. - Document experiments, results, and propose refinements. - Collaborate cross‑functionally to integrate models into production workflows. Required Skills - Strong foundation in mathematics, statistics, and optimization. - Practical experience in machine‑learning and deep‑learning projects, especially in computer vision. - Proficiency in Python programming. - Familiarity with deep‑learning libraries such as TensorFlow and/or PyTorch and hands‑on experience training neural networks. - Ability to implement and adapt algorithms to new problems. - Creative, dynamic, curious mindset with a passion for applying technology to sports analytics. - Particular interest in basketball or football content. Required Education & Certifications - Current student or recent graduate in Computer Science, Electrical Engineering, Applied Mathematics, or a related field. - Coursework or project experience in machine learning, deep learning, and computer vision. - No specific certifications required.

Paris, France

Hybrid

17-11-2025