Location: Munich or Remote (Germany-based)
Industry: Sport-Tech | Start: ASAP | Languages: Fluent English
CUJU is on a mission to become the new digital standard in athlete identification and development in global sports. Our platform harnesses AI, advanced analytics, and digital networking to democratize the access to knowledge, development and career opportunities independent of gender, ethnics or origin. We digitally empower athletes and sports organizations with unbiased and data driven insights on our way to redefine the future of talent scouting.
🌟 Your Mission: As a Computer Vision Engineer, you'll join CUJU’s dynamic AI team, working to develop and enhance innovative computer vision solutions. Your technical expertise will directly impact our core AI products, enabling accurate diagnostics, streamlined user experiences, and removing technical barriers for athletes around the world.
Tasks
What You'll Work On:
* Algorithm Development: Design, develop, and optimize state-of-the-art computer vision algorithms tailored to athlete diagnostics and performance analytics.
* Model Implementation: Implement and refine deep learning models using frameworks such as PyTorch, ensuring accuracy, reliability, and efficiency.
* Integration and Deployment: Collaborate closely with ML Ops, software engineers, and product teams to seamlessly integrate vision models into our products and deploy them at scale.
* Data Processing & Analysis: Process, analyze, and leverage large-scale video and image datasets to continuously improve model performance and accuracy.
* Research & Innovation: Stay abreast of the latest developments in computer vision research, applying insights to enhance CUJU’s competitive edge.
Requirements
🧠What You Bring:
* 5+ years of professional experience developing computer vision algorithms and applications.
* Expert knowledge in deep learning frameworks such as PyTorch, TensorFlow, and familiarity with OpenCV.
* Proven ability to build, train, validate, and optimize deep learning models for image and video analytics.
* Solid programming skills, particularly in Python, with experience in agile software development practices.
* Strong understanding of machine learning fundamentals, image processing, and data pipelines.
* Familiarity with cloud-based infrastructure (AWS, Azure, Google Cloud) and containerization (Docker, Kubernetes).
* Excellent communication and collaboration skills, capable of engaging effectively in international and cross-functional teams.
* Passion for sports, performance analytics, and making a tangible impact through innovative technology solutions.
Benefits
* Opportunity to play a crucial role in an ambitious, fast-growing AI team.
* Competitive compensation, flexible remote work, and dynamic, international team culture.
* Direct collaboration with leading experts in sports technology and football industry stakeholders.
* The chance to pioneer solutions with real-world, global impact in athlete performance analytics.
🎯 Your Impact:
* Develop groundbreaking computer vision solutions that significantly enhance diagnostic accuracy and athlete experience.
* Drive technical innovation, positioning CUJU as a leader in AI-driven sport-tech solutions.
* Directly contribute to products that improve talent evaluation, player safety, and overall athletic performance.
An AI based technology which gives football talents the chance to improve their skills, compete against friends and the global CUJU community and get scouted by a record-proven network of international senior scouts and specialists. At any time, no matter who or where the talents are.
Latest AI technology evaluates, scores, and ranks each athlete in personal spiderwebs and the CUJU leaderboard. International pro players and top-class experts constantly develop new exercises and provide the talents with up-to-date information for the right lifestyle, which helps the talents to constantly improve.
Amateur clubs and football schools on each continent are already using CUJU providing coaches with data-based insights for measuring, improving and comparing their teams.