{"schemaVersion":"jobsearcher.job.v1","id":"d498fcf0d34a5ebcff32851e","url":"https://jobsearcher.com/jobs/d498fcf0d34a5ebcff32851e","canonicalUrl":"https://jobsearcher.com/jobs/d498fcf0d34a5ebcff32851e","title":"Computer Vision Engineer","description":"Role: Senior Applied Computer Vision Engineer (Remote)SUMMARY:We are looking for a Senior Applied Computer Vision Engineer to help build and improve video intelligence solutions for sports. This role is focused on applying computer vision and machine learning techniques to real-world sports video workflows. You will work with exist‐ ing models and pipelines, evaluate performance on new datasets, identify gaps, implement improvements, and partner with engineering teams to deliver production-ready solutions.REQUIRED QUALIFICATIONS:Strong hands-on experience building and improving computer vision systems. Proficiency with Python and modern machine learning frameworks such as PyTorch.Experience working with video-based computer vision problems, including detection, track‐ ing, event recognition, or identity association.Working knowledge of geometric computer vision: camera calibration, homography and pro‐ jective geometry, and mapping image coordinates to real-world coordinates.Experience evaluating model performance, identifying failure modes, and implementing practical improvements.Experience adapting models to challenging real-world data where video quality, camera an‐ gles, and environmental conditions vary significantly, including domain adaptation / transfer learning across different data distributions.Strong software engineering fundamentals and the ability to write maintainable, productionquality code.Ability to work independently, prioritize effectively, and drive projects to completion.PREFERRED QUALIFICATIONS:Experience working with sports video or related domains (American football experience is a strong plus).Experience with large-scale video processing pipelines.Familiarity with tools such as FFmpeg and GPU-accelerated video workflows.Familiarity with OCR / scene-text recognition (e.g., reading jersey numbers or scoreboard graphics).Experience with experiment tracking and model/data versioning (e.g., Weights & Biases, MLflow, lakeFS/DVC).Experience deploying machine learning models into production environments.Experience with model monitoring, performance tracking, and operational support.Experience with human pose estimation (a forward-looking capability for this role).","company":"Programmingcom","rawCompany":"programmingcom","city":"Northern Cambria","state":"PA","isRemote":false,"isActive":false,"createdAt":"2026-07-11T12:26:14.392Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"711211","title":"Sports Teams and Clubs","slug":"sports-teams-and-clubs"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Computer Vision Engineer","description":"Role: Senior Applied Computer Vision Engineer (Remote)SUMMARY:We are looking for a Senior Applied Computer Vision Engineer to help build and improve video intelligence solutions for sports. This role is focused on applying computer vision and machine learning techniques to real-world sports video workflows. You will work with exist‐ ing models and pipelines, evaluate performance on new datasets, identify gaps, implement improvements, and partner with engineering teams to deliver production-ready solutions.REQUIRED QUALIFICATIONS:Strong hands-on experience building and improving computer vision systems. Proficiency with Python and modern machine learning frameworks such as PyTorch.Experience working with video-based computer vision problems, including detection, track‐ ing, event recognition, or identity association.Working knowledge of geometric computer vision: camera calibration, homography and pro‐ jective geometry, and mapping image coordinates to real-world coordinates.Experience evaluating model performance, identifying failure modes, and implementing practical improvements.Experience adapting models to challenging real-world data where video quality, camera an‐ gles, and environmental conditions vary significantly, including domain adaptation / transfer learning across different data distributions.Strong software engineering fundamentals and the ability to write maintainable, productionquality code.Ability to work independently, prioritize effectively, and drive projects to completion.PREFERRED QUALIFICATIONS:Experience working with sports video or related domains (American football experience is a strong plus).Experience with large-scale video processing pipelines.Familiarity with tools such as FFmpeg and GPU-accelerated video workflows.Familiarity with OCR / scene-text recognition (e.g., reading jersey numbers or scoreboard graphics).Experience with experiment tracking and model/data versioning (e.g., Weights & Biases, MLflow, lakeFS/DVC).Experience deploying machine learning models into production environments.Experience with model monitoring, performance tracking, and operational support.Experience with human pose estimation (a forward-looking capability for this role).","datePosted":"2026-07-11T12:26:14.392Z","dateModified":"2026-07-11T12:26:14.392Z","hiringOrganization":{"@type":"Organization","name":"Programmingcom","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Northern Cambria","addressRegion":"PA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"d498fcf0d34a5ebcff32851e"},"url":"https://jobsearcher.com/jobs/d498fcf0d34a5ebcff32851e"}}