Computer Vision Engineer

• Designing, developing, and improving ball and player tracking algorithms using multi-camera systems
• Owning and evolving multi-view geometry solutions for accurate, court-wide tracking
• Developing robust approaches to occlusion handling, recovery, and failure modes in fast-paced sports scenarios
• Enhancing and maintaining mature, long-running computer vision systems used in live production
• Optimising algorithms for performance and reliability, including CPU and GPU considerations
• Contributing to cross-platform systems, ensuring algorithms run consistently across environments
• Supporting the integration of algorithms into cloud-enabled and distributed systems
• Working in an agile environment to deliver robust, production-ready solutions at scale
• Lead the development and improvement of computer vision algorithms from concept through to production
• Design, implement, test, and validate complex algorithmic features
• Take ownership of algorithmic components and drive their long-term maintainability and technical quality
• Collaborate closely with engineers across computer vision, tracking, tooling, and platform teams
• Contribute to technical discussions around architecture, performance, scalability, and deployment
• Identify weaknesses in existing approaches and propose pragmatic improvements
• Share progress, decisions, and learnings with the wider team
• Support and mentor other engineers through code reviews and technical guidance

Senior Computer Vision Engineer focusing on algorithm development for sports tracking systems

Senior Computer Vision Engineer

Senior Computer Vision Engineer developing algorithms for multi-camera sports tracking systems. Join Hawk-Eye Innovations to enhance real-time performance in complex environments.

• Build and improve deepfake and liveness detection models using CNNs, attention layers and vision-language models.
• Design, train and evaluate models end to end, from preparing data to checking results, following good engineering practices.
• Fine-tune vision-language models using efficient methods such as LoRA.
• Make models smaller and faster for both cloud and on-device / mobile use.
• Build and maintain training and deployment pipelines to get models into production on AWS (e.g. EC2, Athena).
• Use AI-assisted coding tools such as Claude Code to speed up experimentation and prototyping.
• Share progress clearly with technical and non-technical colleagues, and own independent research & development initiatives.

Senior Computer Vision Engineer working on deepfake detection models

Senior Computer Vision Engineer developing deepfake and liveness detection models with a cross-functional R&D team in Hungary. Working on a large-scale facial and video database to ensure system integrity and authenticity.

Computer Vision Engineer jobs in Hungary

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Senior Computer Vision Engineer

Senior Computer Vision Engineer