This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Applied Computer Vision Engineer based in Ireland.
Join a highly technical engineering team focused on transforming sports video into actionable insights through advanced computer vision and machine learning. In this role, you will develop, optimize, and scale production-grade vision systems capable of handling complex real-world video environments. You'll work across the full lifecycle of computer vision solutions, from experimentation and model development to deployment and continuous improvement. This position offers the opportunity to solve challenging problems involving object detection, tracking, camera calibration, and video analytics while collaborating with cross-functional engineering teams. The environment is remote-first, flexible, and driven by innovation, giving you the autonomy to lead technical initiatives with meaningful impact.
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Applied Computer Vision Engineer based in Ireland.
Join a highly technical engineering team focused on transforming sports video into actionable insights through advanced computer vision and machine learning. In this role, you will develop, optimize, and scale production-grade vision systems capable of handling complex real-world video environments. You'll work across the full lifecycle of computer vision solutions, from experimentation and model development to deployment and continuous improvement. This position offers the opportunity to solve challenging problems involving object detection, tracking, camera calibration, and video analytics while collaborating with cross-functional engineering teams. The environment is remote-first, flexible, and driven by innovation, giving you the autonomy to lead technical initiatives with meaningful impact.
Accountabilities
- Develop, enhance, and maintain production-ready computer vision models for sports video analytics, including player and ball detection, tracking, event recognition, and identity association.
- Design and improve geometric computer vision solutions such as camera calibration, homography estimation, field registration, and coordinate mapping.
- Evaluate existing computer vision pipelines, identify performance bottlenecks, analyze failure modes, and implement practical improvements to increase accuracy, scalability, and robustness.
- Adapt machine learning models and vision pipelines to support new sports, leagues, stadiums, camera configurations, and varying video quality conditions.
- Design and execute experiments covering dataset creation, augmentation, model training, fine-tuning, evaluation, and production readiness.
- Collaborate with data, software, platform, and DevOps teams to deploy scalable machine learning solutions into production environments while improving inference performance, monitoring, and operational reliability.
- Define evaluation metrics, testing strategies, and quality assurance processes to ensure consistent model performance over time.
- Lead technical initiatives from early research and prototyping through deployment, communicating technical decisions and trade-offs effectively across engineering and stakeholder teams.
- Extensive experience building, deploying, and improving production-grade computer vision systems.
- Strong proficiency in Python and modern deep learning frameworks such as PyTorch.
- Hands-on expertise in video-based computer vision, including object detection, multi-object tracking, event recognition, identity association, or video analytics.
- Solid understanding of geometric computer vision concepts including camera calibration, homography estimation, projective geometry, and mapping image coordinates to real-world environments.
- Experience improving tracking systems in challenging scenarios involving occlusions, noisy detections, identity preservation, and object interactions.
- Demonstrated ability to evaluate model performance, identify weaknesses, and implement effective optimization strategies.
- Experience adapting models to diverse real-world environments using techniques such as transfer learning, domain adaptation, data augmentation, and fine-tuning.
- Strong software engineering practices with the ability to write clean, maintainable, production-quality code.
- Ability to work independently, prioritize multiple initiatives, and drive projects through completion.
- Excellent communication and collaboration skills within cross-functional and client-facing environments.
- Experience in sports analytics, broadcast video, multi-camera systems, GPU-accelerated video processing, OCR, MLOps, backend systems, cloud infrastructure, or technical leadership is considered an advantage.
- Competitive salary based on experience.
- Comprehensive benefits package including paid vacation and sick leave.
- Fully remote position for professionals residing in Europe.
- Flexible working hours with a strong focus on work-life balance.
- Home office equipment allowance and the option to use a coworking space when preferred.
- No business travel required.
- Opportunity to work alongside highly experienced international engineering professionals.
- Collaborative, fast-paced environment with excellent opportunities for technical growth and career development.