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.
But what truly sets us apart? Our people. We’re a diverse group of innovative thinkers, creators, and problem-solvers who believe in delivering an incredible product—and having fun while doing it.
The Opportunity
As a Student Machine Learning Engineer at Veo you will get to work on challenging problems and directly contribute to the value created by our AI-driven end-user products.
You will become part of our AI team, which comprises 12 researchers and engineers that are responsible for all stages in the machine learning lifecycles across different projects - from scoping and defining data annotation tasks to modeling, validation, and deployment. You will work on well-defined tasks that align with the team’s goals, getting guidance and sparring from experienced teammates to the extent you need.
We stay current with the latest research and continuously discuss concepts and ideas in recent papers to assess their relevance to our tasks and product-specific challenges.
We are looking to add an ambitious, high-performing student worker with a strong academic record, experience with multiple machine learning projects, good coding skills, and a passion for the field.
What You Will Do:
- Train state-of-the-art machine learning models
- Write efficient inference pipelines for cloud and edge
- Define and supervise data annotation tasks
- Improve evaluation schemes to increase understanding of model performance and shortcomings
What You Could Bring:
- BSc/MSc ongoing within a relevant field and with a strong academic record
- Hands-on experience with multiple machine-learning projects in Python and PyTorch
- Good coding skills
- Ability to work both independently and as part of a team
Our Copenhagen office mirrors our innovative technology – with an indoor ball court, rooftop terrace, and well-equipped gym. We have created a facility that supports connecting disciplines across the business, facilitates creative thinking, and gives the space to engage with colleagues, our global partners, and the entire Veo community.
Values we hold at Veo:
Dare - We take initiative, stay curious, and challenge the status quo in our work.
Own it - We drive impact by identifying opportunities, taking responsibility, and confidently executing.
Level up - We embrace growth, continuously learning and shaping our skills.
Play as a team - We collaborate across a diverse organization, leveraging shared insights for stronger outcomes.
Customer Centric - We deliver value by having close partnerships and a deep understanding of our customers (internally and externally)
We value diversity and inclusion and welcome applicants from all backgrounds, even if your experience doesn’t completely match every qualification listed. What matters most is your creativity, potential, and ability to contribute meaningfully.
Perks and benefits
This job comes with several perks and benefits
Free lunch
Flexible working hours
Free coffee / tea
Social gatherings
Free office snacks
Free friday beers
Working at
Veo Technologies
Veo is the world’s leading AI powered and affordable football camera solution. We want to enable all teams around the world recording their football matches without the obstacles of finding a cameraman. Democratizing football, by giving access to video analysis, that in the past only were available for the few.
The innovative dual-lense camera technology records the entire pitch at all times, with two 4K high resolution sports action lenses. Our intelligent software automatically follows the ball to create a broadcast view, while allowing you the controls with a simple click of you mouse. Our solution is developing better athletes. We know players are visual learners, seeing themselves play rather than being told of their mistakes is more effective and likely to produce results.
