Computer Vision Engineer

Aviso de fuente externaen Programming.com

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 spor...

Fuente externa - sin verificarhace 12 díasVigente hasta: 8 sep 2026

Salario

No especificado

Ubicación

Mexico City, Mexico

Tipo de empleo

Tiempo completo

Modalidad

No especificado

Computer Vision Engineer

Mexico City, Mexico

Descripción del empleo

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).

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