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Veo

Posted 7 months ago

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Student Worker - Machine Learning Engineer

CopenhagenOn-siteFull-time

AI Summary

Student ML Engineer at Veo works on training models, building inference pipelines, and supervising data annotation tasks as part of a small AI team.

About this role

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
  • Ability to work onsite from the Copenhagen office 1 or 2 days per week
  • 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

    • Skills

    CloudData AnnotationDeep LearningDeploymentEdgeGitInference PipelinesMachine LearningModel EvaluationPythonPyTorchResearchSciKit-LearnTraining PipelinesValidation

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