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Computer Vision Data Scientist

Sweden, Stockholm · Job Posted January 11, 2026
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Job Description

As a Data Scientist, with focus on Computer Vision, you’ll be training AI models and evaluate if the model is learning and picking up the pattern it should. Your focus will initially be to retrain existing models when there is more data available to train on. Arkion has a steady flow of new images and new annotations on these images that can be curated and used for retraining jobs. But as soon as you are ready and know the data science team’s platforms, tools and the datasets, we will want you to develop new models and solve problems nobody has solved before.

Job Responsibility

  • Evaluate models on test data and real world data
  • Retrain existing AI models
  • Train the first version of new AI models
  • Evaluate new AI frameworks and AI model architectures to reach higher performance
  • Monitor live model performance on real-world sensor data streaming into our platform for the models you trained
  • Mentor our annotation team, trimming our internal processes to ensure consistently high-quality annotations that have high signal to noise ratio
  • Debate improvements of precision and recall with colleagues and the customers’ data science teams
  • Research areas that Arkion need to cover to stay up to date with Computer Vision industry improvements

Requirements

  • Problem solving skills for anything software
  • Degree in engineering
  • Machine learning education
  • Experience with Python and SQL
  • A sharp eye for details
  • Experience doing annotations for Computer Vision
  • Excellent written and spoken English

Nice to have

  • Computer Vision experience
  • Knowledge of electrical grids
  • Experience working in fast-paced, international environments

What we offer

  • Impact that matters: your work directly increases grid reliability and supports the energy transition
  • Real ownership: meaningful scope, visible outcomes, and room to grow as we scale
  • A strong and supportive team: collaborative, international colleagues with deep domain and technical expertise

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