Sr Deep Learning(Computer Vision) Engineer Offline

As a Sr Deep Learning Engineer (Computer Vision), you will play a crucial role in processing and analyzing sports data to power innovative streaming solutions. This is a fully remote position, offering flexibility and the opportunity to collaborate with a global team.

Time Zone: Team primarily based in Ukrainian Time Zone, with occasional evening syncs (17:00–18:00 UTC+3) with the USA team.

100% of the engineering team from UKR

About Us: We are a dynamic streaming company specializing in sports data, focusing on basketball and soccer. Our mission is to deliver exceptional AI-driven solutions that enhance the sports viewing experience. Join our team and contribute to cutting-edge projects that merge sports and technology!

Responsibilities:

• Prepare and preprocess sports data (e.g., basketball and soccer) for training computer vision models.

• Perform quality assurance (QA) on model outputs and results to ensure high accuracy and reliability.

• Design and run experiments to improve model performance for real-world applications.

• Collaborate with international teams to develop and deploy cutting-edge computer vision solutions.

Requirements:

• Strong understanding of deep learning principles and their application to computer vision.

• Proficiency in Python programming, with experience in writing clean, efficient, and maintainable code.

• Hands-on experience with major computer vision libraries (e.g., OpenCV, scikit-image).

• Familiarity with deep learning frameworks such as PyTorch, TensorFlow, or Keras.

• Knowledge of key computer vision tasks, including object detection, image segmentation, classification, and tracking.

• Ability to work collaboratively in a remote team environment, accommodating time zone differences.

Nice-to-Have Skills:

• Experience with MMDetection and the OpenMMLab ecosystem.

• Familiarity with CI/CD tools (e.g., GitHub Actions, Jenkins) for automating workflows.

• A passion for sports analytics and a solid understanding of basketball or soccer dynamics.