ML and Computer Vision Engineer

Vor 7 Tagen


Berlin, Berlin, Deutschland Covelant Vollzeit 60.000 € - 120.000 € pro Jahr

Company Description

Covelant is an innovative sports analytics startup based in Germany, driven by the mission to make elite performance tools accessible to athletes and coaches at all levels. Our advanced yet affordable technology delivers real-time performance analysis, predictive insights, and error detection to empower athletes and optimize performance. Focused on growth and innovation, Covelant strives to level the playing field in sports with accessible, cutting-edge tools. At Covelant, we are passionate about helping athletes achieve their full potential through smarter and faster improvement.

Role Description

This is a full-time position for a Machine Learning and Computer Vision Engineer, based on-site in Berlin. The role involves designing and implementing advanced machine learning and computer vision solutions tailored to real-time sports analytics. Responsibilities will include developing and optimizing algorithms for pattern recognition, analyzing datasets, collaborating with cross-functional teams, and refining models to achieve high accuracy and performance. You will contribute to building innovative tools for enhancing athletic performance while staying engaged with the latest advancements in the fields of machine learning and computer vision.

Qualifications

  • Strong foundation in Computer Science, Data Science, and related technical disciplines
  • Expertise in Machine Learning, Computer Vision, and Pattern Recognition techniques
  • Experience with Robotics and developing solutions for real-time applications
  • Proficiency in programming languages such as Python or similar, with experience in frameworks like TensorFlow or PyTorch
  • Ability to work collaboratively within a team to achieve innovative solutions
  • Strong problem-solving skills and the ability to tackle complex challenges
  • Previous experience in sports analytics or high-performance computing is a plus
  • Master's or Ph.D. in a relevant field is preferred


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