Computer Vision Data Scientist — Train & Improve AI Models

Arkion

Stockholms kommun

Presencial

SEK 491.695 - 764.859

Jornada completa

14 días+
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Ventajas ofrecidas por este puesto de trabajo

Collaborative international team
Impactful work in energy transition
Room to grow as the company scales

Descripción de la vacante

A data-driven technology firm is seeking a Data Scientist focusing on Computer Vision to train and evaluate AI models using one of the largest datasets in the industry. You will work on-site in Stockholm, Sweden, collaborating closely with the annotation team and ensuring high-quality data for model training and performance. The ideal candidate will have experience in Python, SQL, and Machine Learning, alongside a passion for data quality. This full-time position offers meaningful ownership and impact in the energy transition.

Formación

  • Passionate about data quality and supervised learning.
  • Ability to mentor annotation teams and improve annotation quality.

Responsabilidades

  • Evaluate models on test data and real-world data.
  • Train new AI models and evaluate frameworks for higher performance.
  • Monitor live model performance on real-world sensor data.
  • Debate improvements of precision and recall with teams.
  • Research industry improvements in Computer Vision.

Conocimientos

Problem solving skills
Experience with Python
Experience with SQL
Experience doing annotations for Computer Vision
Excellent written and spoken English

Educación

Machine learning education

Descripción del empleo

A data-driven technology firm is seeking a Data Scientist focusing on Computer Vision to train and evaluate AI models using one of the largest datasets in the industry. You will work on-site in Stockholm, Sweden, collaborating closely with the annotation team and ensuring high-quality data for model training and performance. The ideal candidate will have experience in Python, SQL, and Machine Learning, alongside a passion for data quality. This full-time position offers meaningful ownership and impact in the energy transition.
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