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Machine Learning Engineer (Computer Vision) - Sport domain

Machine Learning Engineer (Computer Vision) - Sport domain

Opinov8UA
30+ днів тому
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PROJECT DESCRIPTION :   Our client is an innovative leader in professional sports entertainment in Germany, focused on delivering high-energy competitions and enhancing fan engagement.

With a commitment to creativity and collaboration, the organization is redefining the sports experience while providing a platform for talented athletes to showcase their skills.

We are seeking a skilled Machine Learning Engineer specializing in Computer Vision to develop AI-powered solutions for analyzing football drills from video footage.

You will work with deep learning models, computer vision techniques, and cloud-based ML deployment to extract real-world insights from sports videos.

  • IN THIS ROLE, YOU WILL : - Design, develop, and optimize a Computer Vision part of the solution for analyzing football drills in video footage; - Post-process model outputs using mathematical methods to derive real-world metrics (distance, speed, acceleration, etc.); - Train and fine-tune deep learning models; - Preprocess and augment video data using OpenCV and related libraries; - Collaborate with cross-functional teams to integrate models into a production environment.
  • IF YOU HAVE :   - Strong experience in Computer Vision, including object detection, segmentation, tracking, keypoint / pose estimation, action recognition, and depth estimation; - Proficiency in Python and deep learning frameworks such as PyTorch; - Hands-on experience with YOLO and Transformer-based architectures for vision tasks; - Expertise in image and video processing using OpenCV; - Experience with cloud ML deployment, preferably using AWS SageMaker; - Strong understanding of model training, evaluation, and optimization; - Strong problem-solving skills and ability to work independently.
  • NICE TO HAVE :   - Experience applying machine learning to biomechanics, physical exercise analytics, and human motion analysis; - Knowledge of AWS infrastructure and MLOps best practices; - Experience deploying edge AI models on mobile platforms (Android / iOS).

AS AN OPINOV8R, YOU WILL HAVE :   -  Digital-First Approach :   Great talent knows no borders!

You can work from wherever you are.

We hire and collaborate with professionals worldwide; -  Remote Work Model :  Balance your professional and personal life with our flexible working conditions.

We offer an equal and transparent working environment, empowering you to be productive and deliver your best from anywhere; -  Flexible Time-Off Policy :  Enjoy twenty vacation days, long and short-term sick leave, and five extra personal days to take care of important personal matters, allowing you to manage your time as you see fit; -  Exciting Projects :  Dive into impactful projects across various industries that challenge and spark your creativity.

Work on innovative solutions that push boundaries, giving you the chance to make a difference and drive change; -  Boost Your Expertise :   Elevate your career with unmatched experiences that expand your knowledge and master skills.

We foster continuous learning and development opportunities that allow you to grow and reach new heights; -  Join the Best Team Ever :  Collaborate with our diverse and сross-cultural team of passionate technologists and creative thinkers who inspire and support.

Together, we develop services that make a real impact on the world.

HOW’S THE HIRING PROCESS GOING : We strive to make a smooth and transparent hiring process to find the perfect match for both sides.

Steps may differ depending on the position — here's what to expect :       - Initial Interview :   If your background fits the role's criteria, we'll invite you for an interview with a Talent Acquisition Specialist to get to know you better;  - Technical Interview :   Depending on the role, you may be asked to complete a technical assessment / test tasks to showcase your expertise; -   Final Decision :  After completing all interviews and assessments, we'll reach a final decision and get back to you with the result.

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Machine Learning Engineer • UA