
Computer Vision Engineer
Posted Jun 3

Posted Jun 3
This is a fully remote position, open to applicants in United States.
β’ Take charge of the design and implementation of sophisticated computer vision models β including object detection, multi-object tracking, camera calibration, and semantic segmentation β aimed at player tracking across various sports.
β’ Develop and enhance high-performance pipelines for the ingestion, processing, and analysis of video and image data, ensuring they meet the rigorous demands of professional and collegiate programs.
β’ Engage in the entire computer vision and machine learning lifecycle, from data collection and model development to training, production deployment, monitoring, and continuous improvement.
β’ Lead research and development projects focused on 3D body pose tracking, real-time analytical systems, and integration with large language models and natural language processing research β with significant freedom to innovate within each projectβs framework.
β’ Work collaboratively with Software Engineering, Product, and Data Operations teams to guarantee that your contributions are effectively understood, incorporated, and utilized downstream.
β’ Practical expertise in Python, PyTorch, and OpenCV for deploying computer vision applications in production β beyond just research prototypes.
β’ Proven track record of guiding computer vision and machine learning models through the complete lifecycle: development, training, evaluation, deployment, and ongoing enhancement within real-world systems.
β’ Capability to design and create modular, maintainable software architectures for intricate computer vision and machine learning pipelines β this team focuses on building systems rather than just models.
β’ Experience in cloud computing with AWS or similar platforms, along with a solid understanding of Linux environments and CUDA for GPU optimization.
β’ Strong ability to convey complex technical concepts clearly to non-technical stakeholders β itβs essential that other teams understand what youβve created and the rationale behind it when they utilize your outputs.
β’ Equity offerings available.
β’ Bonus opportunities provided.
Julesetmoi
National University
MeridianLink
Woolpert
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