About Us:
Driblab analyzes football performance using advanced data and technology. Every football game generates thousands of data points — from simple statistics like shots and assists to complex metrics — which we process into models that objectively evaluate player performance. Our platform covers over 180,000 players across 180+ professional leagues, helping clubs, agents, and federations minimize risk and maximize returns. driblab.com
Role Overview:
We’re looking for a motivated junior or mid-level engineer to join Driblab as a Data Science, Web Development, and Machine Learning & Computer Vision Intern in Madrid. You will work hands-on with large football datasets, develop models, and contribute to web applications that deliver actionable insights to football professionals worldwide. This is a paid internship offering real experience in sports analytics, AI, and software development.
Key Responsibilities:
Process and analyze large football datasets to extract meaningful insights. Develop and implement machine learning models, including computer vision applications for player performance analysis. Assist in web development projects, integrating data and analytics into user-facing platforms. Collaborate with the team to improve existing models, algorithms, and data pipelines. Conduct research to support new analytical methods and performance metrics. Participate in testing, debugging, and documentation of tools and applications.
Requirements:
Currently studying or recently graduated in Computer Science, Data Science, Software Engineering, AI, or a related field. Strong programming skills in Python, JavaScript, or relevant languages. Familiarity with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). Basic understanding of computer vision and data analytics concepts. Analytical mindset with problem-solving skills. Interest in football and sports analytics.
Preferred:
Experience with web development frameworks. Knowledge of database management and data visualization tools. Prior work or projects involving machine learning or computer vision. Understanding of football statistics and performance metrics.
What You’ll Gain:
Hands-on experience in data science, machine learning, computer vision, and web development applied to sports analytics. Opportunity to work with large, real-world datasets in a global football context. Exposure to the workflows and decision-making of football clubs, agents, and federations. Mentorship from experienced engineers and analysts. Paid internship with the chance to make a tangible impact on products and models.