Spyrosoft is an industry leader in the media and entertainment sector, dedicated to elevating the global viewing experience through innovative technologies. As a thriving, inclusive environment, Spyrosoft values creativity, technical excellence, and collaboration in developing cutting-edge front-end solutions and system integrations. Our diverse team applies advanced software engineering and AI to bring accessible and engaging products to viewers around the world.

We are currently seeking a highly skilled Computer Vision AI Engineer whose expertise will help us deliver next-generation intelligent applications for our global audience.

Requirements: 

• Minimum 4 years of professional experience in computer vision, artificial intelligence, or machine learning engineering roles
• Advanced proficiency with deep learning frameworks such as TensorFlow, PyTorch or Keras
• Solid foundation in computer vision algorithms (image classification, object detection, tracking, segmentation, etc.)
• Strong skills in Python programming, experience with libraries such as OpenCV, NumPy, and Scikit-learn
• Experience developing and deploying computer vision models to production environments
• Fluency in written and spoken English (C1 or above) is required
• Ability to communicate complex technical concepts clearly within cross-functional teams
• Capability to work independently as well as collaboratively, with a proactive and solution-oriented approach

Nice to have: 

• Professional experience in the media and entertainment, video streaming, or smart TV sectors
• Practical background in video analytics, facial recognition, action recognition, or scene analysis
• Familiarity with cloud platforms (e.g. AWS, GCP, Azure) and containerisation (Docker, Kubernetes)
• Knowledge of edge computing or real-time video processing systems

Responsibilities:

• Designing, developing, and optimising AI computer vision models for media and video analysis use cases
• Collaborating with software engineering, product, and UX teams to define requirements and deliver best-in-class AI features
• Implementing end-to-end solutions, including data collection, model training, evaluation, and deployment
• Analysing results and iterating on model improvements to ensure optimal accuracy, speed, and reliability
• Documenting processes and knowledge sharing within the team to foster continuous improvement and innovation
• Staying up-to-date on the latest advancements in computer vision, deep learning, and AI software engineering