ironquill.tech/board

$ cat jobs/sports-computer-vision-engineer-sumersports-llc-46b7de917c6d.json

Sports Computer Vision Engineer

sumersports llc·US·United States·mid
mlcomputer vision
Apply on himalayas → Get AI match score →
SumerSports is a leading football intelligence technology company that specializes in providing an innovative suite of products for football fans and NFL clubs. We are a collection of executives, engineers, data scientists, and visionaries from NFL clubs, technology startups, finance, and academia. Our data-driven platform empowers teams with insights and tools to make informed decisions within salary cap constraints. The platform also serves the NCAA, offering insights around the transfer portal and more. What sets us apart is our unique blend of big tech talent, data scientists, and former NFL personnel, who have a combined 600+ years of NFL experience. Our domain knowledge is augmented by AI and machine learning technologies to create a unique view into many aspects of Football. We’re hiring a hands-on Computer Vision Engineer to build and improve sports video intelligence models—detection, tracking, pose, event understanding, and multi-view reasoning. You’ll spend most of your time on CV research + applied modeling (experiments, architectures, training, evaluation), and partner with data/platform teammates to ensure your work can ship reliably. This role is CV-first. A bend toward scalable pipelines / MLOps is a plus, not a requirement. Level (mid vs senior) depends on scope ownership and how independently you can drive results. Responsibilities CV Modeling & Experimentation Build and train CV models for sports video: player/ball detection, multi-object tracking, pose/keypoints, event/action recognition, identity association (re-ID). Own the experimentation loop: hypotheses → ablations → error analysis → measurable improvements. Design and maintain evaluation: task-appropriate metrics (e.g., MOT metrics, keypoint accuracy, event precision/recall), dataset slices, and failure taxonomy. Improve data efficiency: augmentations, sampling strategies, handling label noise, weak/self-supervision where helpful. Prototype and iterate on modern architectures (e.g., transfo

Similar remote roles

Business Development Manager, Central Region
CompScience · US · mid
Data Scientist (Search & Recommendation)
binance · APAC · mid
Machine Learning Engineer
Code Compass 🧭 · Worldwide · mid
Machine Learning Engineer*
TOMRA · Worldwide · mid
Consultant – Compliance Data Science & AI
Sia · US · mid
Consultant- Marketing Data Science & AI
Sia · US · mid
Consultant- Marketing Data Science & AI
Sia · US · mid
Consultant – Compliance Data Science & AI
Sia · US · mid