Machine Learning Student Worker

Veo is a global leader in AI-based sports camera technology. Our innovative, fully automatic camera solution enables sports teams to record matches and training sessions without a camera operator. We’re democratizing the world of sports by granting video analysis for teams on all levels—a privilege that used to be only for the few. More than 40,000 clubs in 90+ countries record their games every week.

Working as a student assistant in Veo’s AI team is evolving, challenging, and exciting. You’ll be collaborating with skilled and experienced full-time ML researchers and engineers while getting the chance to take responsibility for your projects. At the same time, you’ll never be left alone but get good support from the rest of the team when facing challenges. This creates a suitable environment for a student worker to develop new skills technologically, theoretically, and operation-wise.

Primary tasks:

• Develop machine learning models from scratch.
• Improve existing models and apply them to new data.
• Acquire knowledge of innovative research within different machine-learning areas.
• Scope projects and goals.
• Make further explorations on machine learning in sports environments.
• Do data analysis.
• Use standard software practices to improve development and machine learning operations.

Requirements:

Good theoretical foundations in machine learning and (preferably) computer vision. Comprehensive skills in Python and machine learning libraries. Experience with classic software development concepts like git, servers, GPUs, and cloud services.

Diversity and differences are valuable assets for us. We value diversity and inclusion and welcome people from all backgrounds. If you’re excited about this role but your experience doesn’t align perfectly with every qualification in the job description, we still encourage you to apply.

We’re committed to building a diverse, inclusive, and authentic workplace. And you may be just the right candidate for this or other roles.

We will invite for interviews continuously, so apply with LinkedIn or your resume as soon as possible.