Computer Vision Engineer

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🕒 May 31

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SumerSports

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2022

⚽ Sports

🤖 Artificial Intelligence

☁️ SaaS

Sports • Artificial Intelligence • SaaS

SumerSports is an AI-powered sports analytics and technology company focused on football (NFL and NCAA). Combining over 500 years of NFL experience with machine learning, SumerSports offers products such as SūmerBrain for film retrieval and multi-layered data, SūmerLive for game tracking, SūmerNFL and SūmerNCAA for roster building and team optimization, and a player-verified metrics and talent exposure platform. The company produces draft guides, analytics-driven content with former scouts and Hall of Famers, and tools that serve players, teams, and fans to improve scouting, roster decisions, and performance evaluation.

📋 Description

• 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., transformer-based detection/tracking, temporal models, multi-task setups). • Collaborate on dataset + labeling design: formats, schemas, tooling, versioning. • Help productionize models: packaging, batch/stream inference patterns, throughput/latency tradeoffs, robustness checks. • Add lightweight quality gates: reproducibility, automated eval, regression detection.

🎯 Requirements

• Strong applied CV experience with hands-on model development (not just running existing repos). • Solid PyTorch skills: training loops, debugging, data pipelines for vision workloads, DDP basics. • Comfort with video CV fundamentals: occlusion, identity switches, temporal consistency, calibration, domain shift. • Strong Python engineering and a bias toward measurable outcomes. • Nice-to-have (Bonus): Sports video CV or adjacent domains (multi-agent tracking, pose, crowded scenes). • Experience with video tooling (FFmpeg), efficient dataset formats (WebDataset/shards), or streaming/batching to GPUs. • MLOps/production experience: model packaging, CI for training/eval, serving (Triton/TorchServe), monitoring.

🏖️ Benefits

• Comprehensive health insurance plan • Retirement savings plan (401k) with company match • Generous paid holiday schedule - 13 in total including Monday after the Super Bowl • Remote working environment