Senior Applied Computer Vision Engineer

Senior Applied Computer Vision Engineer

Janea Systems is looking for a Senior Computer Vision Engineer to join our team and support one of our clients in the sports analytics industry. In this role, you will help design, improve, and scale computer vision systems that transform sports video into actionable insights. The work will focus on video-based detection, tracking, camera calibration, homography, field registration, identity association, and adapting existing models and pipelines to new video sources, camera configurations, stadiums, and video-quality conditions.

This is a highly hands-on technical role for someone who combines strong computer vision fundamentals with practical engineering experience and the ability to drive initiatives from experimentation through production deployment. The ideal candidate is comfortable working independently, identifying weak points in existing systems, designing practical improvements, and collaborating with engineering, data, and platform teams to deliver production-ready solutions.

Qualifications

• Strong hands-on experience building and improving production-grade computer vision systems.
• Proficiency with Python and modern machine learning frameworks such as PyTorch.
• Experience with video-based computer vision problems, including object detection, multi-object tracking, event recognition, identity association, or video analytics.
• Strong working knowledge of geometric computer vision, including camera calibration, homography estimation, projective geometry, and mapping image-space detections to real-world 2D or 3D coordinates.
• Experience designing or improving tracking systems that handle occlusions, object interactions, identity preservation, noisy detections, and missing information.
• Experience evaluating model performance, identifying failure modes, and implementing practical improvements.
• Experience adapting models to challenging real-world data where video quality, camera angles, camera placement, and environmental conditions vary significantly.
• Experience with transfer learning, domain adaptation, data augmentation, and fine-tuning models on domain-specific datasets.
• Strong software engineering fundamentals and the ability to write clean, maintainable, production-quality code.
• Ability to work independently, prioritize effectively, and drive technical initiatives to completion.
• Strong communication skills and the ability to collaborate directly with clients and cross-functional engineering teams.

Ideal candidates will also have

• Experience working with sports video, sports analytics, broadcast video, or American football.
• Experience with multi-camera systems, image fusion, or 3D scene reconstruction.
• Experience with large-scale video processing pipelines.
• Familiarity with FFmpeg, GPU-accelerated video workflows, and inference optimization.
• Experience with OCR, scene-text recognition, jersey-number recognition, or appearance-based re-identification.