SkillCorner

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

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

Company Name

SkillCorner

Job Title

Director of AI – Predictions

Job Description

**Job title:** Director of AI – Predictions **Role Summary:** Lead the data science organization focused on predictive analytics for elite sports teams. Own the AI roadmap, drive end‑to‑end project delivery, and act as the primary technical liaison for clients and cross‑functional partners. **Expectations:** * Deliver high‑impact predictive solutions that transform performance analysis, scouting, and recruitment. * Translate client objectives into measurable data products and integrate them into existing workflows. * Maintain the highest standards of quality, scalability, and model interpretability. **Key Responsibilities:** * Build and mentor a team of data scientists, fostering a culture of experimentation and continuous learning. * Define the long‑term AI strategy, prioritizing initiatives that align with business goals and product roadmaps. * Oversee project execution: scope, timelines, resource allocation, and stakeholder communication. * Serve as the senior technical point of contact for current and prospective clients, ensuring customer success and adoption. * Collaborate with product managers, sales, engineers, and computer vision experts to design and validate predictive features. * Provide hands‑on guidance for complex modeling challenges, especially deep‑learning techniques applied to sports tracking data. **Required Skills:** * Minimum 4 years of experience managing data science teams in a product‑driven, fast‑paced environment. * Proven track record in defining technical roadmaps and leading multi‑stakeholder projects. * Deep expertise in machine learning, with a focus on predictive modeling and deep‑learning deployment. * Solid understanding of sports analytics, including match analysis, scouting, and recruitment workflows. * Direct experience working with professional sports clubs or in a related stakeholder ecosystem. * Excellent communication skills—ability to explain technical concepts to non‑technical audiences. * Fluent in English. **Bonus Skills:** * Experience creating and processing event data and player tracking data. * Hands‑on training and deployment of deep‑learning models in production environments. **Required Education & Certifications:** * Bachelor’s degree (or equivalent) in Computer Science, Data Science, Statistics, Engineering, or related field. * Master’s degree or relevant certifications (e.g., ML/AI specializations, deep‑learning credentials) preferred but not mandatory.

Paris, France

Hybrid

Junior

17-12-2025

Company Name

SkillCorner

Job Title

ML Ops/Engineer

Job Description

**Job Title:** ML Ops Engineer **Role Summary:** Bridge the Software and Data Science teams to enable scalable, reproducible development, testing, and production deployment of machine learning models. Drive end‑to‑end ML lifecycle management, optimize model performance and cloud costs, and support data scientists in adopting best practices. **Expectations:** - Deliver reliable, production‑ready ML tooling and pipelines. - Ensure model reproducibility, versioning, and traceability. - Optimize computational efficiency and cloud resource utilization. - Collaborate closely with data scientists and engineering peers. - Contribute to a fast‑moving tech startup environment with high motivation and ownership. **Key Responsibilities:** - Design and implement infrastructure for training and testing ML models at production scale (Docker, EKS, Step Functions, etc.). - Manage the full ML lifecycle: data, model, code, and deployment artifacts. - Optimize neural networks and algorithms to reduce compute time and cloud spend. - Provide guidance and tooling to data scientists for best‑practice ML development. - Integrate models into the existing stack (Python, TensorFlow, PyTorch, ONNX, TensorRT, Django, Angular). - Monitor model performance and health using Grafana and related observability tools. - Maintain CI/CD pipelines (GitLab, pre‑commit, Poetry/UV, pytest) for ML projects. **Required Skills:** - Strong Python programming proficiency. - Deep theoretical and practical knowledge of Machine Learning. - Expertise with ML frameworks: TensorFlow, PyTorch, ONNX, TensorRT, CUDA ecosystem. - Hands‑on experience with Docker and Kubernetes/EKS (or equivalent orchestrators). - Familiarity with AWS services (EC2, EKS, RDS, Lambda) or other major cloud platforms (GCP, Azure). - Proficient with Linux environments and Git version control. - Ability to design reproducible training pipelines and model versioning. **Required Education & Certifications:** - Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related technical field (or equivalent practical experience). - Relevant certifications (e.g., AWS Certified Solutions Architect, Certified Kubernetes Administrator) are a plus but not mandatory.

Paris, France

Hybrid

21-01-2026